A Proposed Heuristic for a Computer Chess Program€¦ · to play a stronger positional game of...

A Proposed Heuristic for a Computer Chess Program

copyright (c) 2012John L. Jerz

[email protected], Virginia

Independent ScholarMS Systems Engineering, Virgina Tech, 2000

MS Electrical Engineering, Virgina Tech, 1995BS Electrical Engineering, Virginia Tech, 1988

May 8, 2012

Abstract

How might we manage the attention of a computer chess program in orderto play a stronger positional game of chess? A new heuristic for estimating thepositional pressure produced by chess pieces is proposed. We evaluate the ’health’of a game position from a Systems perspective, using a dynamic model of theinteraction of the pieces. The identification and management of stressors and theconstruction of resilient positions allow effective cut-offs for less-promising gamecontinuations due to the perceived presence of adaptive capacity and sustainabledevelopment. We calculate and maintain a database of potential mobility foreach chess piece 3 moves into the future, for each position we evaluate. Wedetermine the likely restrictions placed on the future mobility of the pieces basedon the attack paths of the lower-valued enemy pieces. Knowledge is derived fromFoucault’s and Znosko-Borovsky’s conceptions of dynamic power relations. Wedevelop coherent strategic scenarios based on guidance obtained from the lowest-scoring of the vital Vickers/Bossel/Max-Neef diagnostic indicators. Initial resultsare presented.

keywords: complexity, chess, game theory, constraints, heuristics, planning,measurement, diagnostic test, resilience, orientor

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A Proposed Heuristic - copyright (c) 2012 John L. Jerz

Contents

1 Overview 5

2 Introduction 5

3 Principles of Positional Chess 6

4 Systems Engineering 8

5 Systems Thinking 9

6 Goldratt’s Theory of Constraints and Thinking Process 10

7 Soft Systems Methodology 11

8 Measurement 12

9 Vulnerability 13

10 Resilience 14

11 Inventive Problem Solving 16

12 Strategy and the Strategic Plan 17

13 Competitive Intelligence Leads to Competitive Advantage 26

14 From Orientors to Indicators to Goals 28

15 Shannon’s Evaluation Function 34

16 The Positional Evaluation Methodology 35

17 Observations from Cognitive Science 42

18 Serious Play Can Lead to Serious Strategy 43

19 John Boyd’s OODA Loop 49

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20 Adaptive Campaigning model of Grisogono and Ryan 50

21 Bent Flyvbjerg’s ”OODA Loop” 51

22 Endpoint Evaluation 51

23 Complexity 53

24 Uncertainty 54

25 Narrative Rationality 55

26 Results 57

27 Conclusions 60

28 Appendix A: Selective Search and Simulation 66

29 Appendix B: The Importance of Sustainability 67

30 Appendix C: Related Quotations 68

References 70

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Life is more fun if you play games.

-Roald Dahl

I would like to try out an idea that may not be quite ready, indeed may not be quitepossible. But I have no doubt it is worth a try. It has to do with the nature of thoughtand with one of its uses... For the last several years, I have been looking at another kindof thought... one that is quite different in form from reasoning: the form of thoughtthat goes into the construction not of logical or inductive arguments but of stories ornarratives.

-Jerome Bruner

There is a story which I have used before and shall use again: A man wanted to knowabout mind, not in nature, but in his private large computer. He asked it (no doubtin his best Fortran), ”Do you compute that you will ever think like a human being?”The machine then set to work to analyze its own computational habits. Finally, themachine printed its answer on a piece of paper, as such machines do. The man ran toget the answer and found, neatly typed, the words:

THAT REMINDS ME OF A STORY

-Gregory Bateson

We dream in narrative, day-dream in narrative, remember, anticipate, hope, despair,believe, doubt, plan, revise, criticize, construct, gossip, learn, hate and love by narrative.In order really to live, we make up stories about ourselves and others, about the personalas well as the social past and future. This long, incomplete and obvious list... points tothe narrative structure of acts of mind

-Barbara Hardy

thinking in terms of stories must be shared by all mind or minds... Context and relevancemust be characteristic... of all so-called behavior (those stories which are projected outinto ”action”)

-Gregory Bateson

To solve problems that blind spots have made unsolvable, people need new perceptualframeworks that portray the problematic situations differently.

-William Starbuck, Frances Milliken

A writer may try his best to draw a map of how things are, that will be equally validfor all; but all he can really do is to paint a picture of what he sees from the unique andtransient viewpoint which is his alone... It is for the reader to say how much my viewcontributes to his own.

-Geoffrey Vickers

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1 Overview

The complexity present in the game of chess of-ten hinders planning efforts and makes simplequestions like ”what’s going on?” and ”whichside has the better position?” difficult to answer.

Indeterminate and unexpected events in thenear future might make revisions necessary forthese plans, often after only a few moves havebeen played.

We theorize that dynamic planning modelsbased on perceptions of constraints, the man-agement of stress, the readiness of resources tosupport strategy, resiliency, sustainable develop-ment, narrativity, and sensitivity to both incre-mental progress towards goals and the emergenceof new opportunities can be used with greatersuccess. We seek positions which can serve as aplatform for future success, in a future that isoften uncertain.

A proposed heuristic for a machine playingthe game of chess, taking advantage of conceptsfrom multiple disciplines, can be used to bet-ter estimate the potential of resources to supportstrategy and to offer better insight for determin-ing whether progress is being made towards re-mote goals. In a future that is uncertain, thereis a benefit to develop a strategic position fullof resilience, flexibility, and structures with thepotential for seizing new opportunities as theyemerge.

As we evaluate each game position and ori-ent our diagnostic exploration efforts, we nowconsider the potential to exploit and respond tonew opportunities as time passes and new situ-ations emerge from beyond our initial planninghorizon. Our flexibility ideally allows a smoothand resilient response to concurrent events asthey unfold. We theorize that our focus on the

constraints, as well as the development of a re-silient position, is a more useful level of abstrac-tion for our game-playing machine.

We examine concepts and values useful forplaying a positional game of chess, we developa perception useful for measuring incrementalprogress towards goals, and then look at po-sitions in chess games where the heuristic of-fers insight not otherwise obtainable. We con-clude that our orientation/evaluation heuristicoffers promise for a machine playing a game ofchess, although our limited evidence (at present)consists of diagrams showing the strategic (dy-namic) potential of the game pieces and an ex-ample of how these ’building blocks’ can be com-bined into vital indicators.

We see the chess position as a complex adap-tive system, full of opportunities of emergencefrom interacting pieces. Our aim in this paperis to reengineer the work performed by our ma-chine, mindful of the values commonly adoptedby experts and the principles of Systems think-ing, so that it might be done in a far superiorway (Hammer and Stanton, 1995).

2 Introduction

This paper is concerned with heuristic algo-rithms. According to (Koen, 2003) a heuristicis anything that provides a plausible aid or di-rection in the solution of a problem but is inthe final analysis unjustified, incapable of justifi-cation, and potentially fallible. Heuristics helpsolve unsolvable problems or reduce the timeneeded to find a satisfactory solution.

A new heuristic is proposed which offersbetter insight on the positional placement ofthe pieces to a chess-playing computer program.

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The heuristic will have usefulness in the orienta-tion/evaluation methodology of a computer pro-gram, or as part of a teaching tool which explainsto a human user the reasons that one side or theother has an advantage in a chess game.

To the extent that a story can be told aboutthe world around us, sense can be made ofits complex relationships, and judgments canbe levied upon them. The mental acts of un-derstanding and judging, cognitive psychologistssuggest, is achieved through the organization ofperceptions into narrative format, and, subse-quently, the integration of newly acquired nar-ratives into available, already internalized tales(Thiele, 2006). This capacity arises because nar-rative, and narrative alone, allows us to forgea coherent temporal/historical context for exis-tence while making sense, and justifying, actionsin terms of plans and goals (Thiele, 2006).

Computer chess programs have historicallybeen weak in understanding concepts relating topositional issues. The proposed heuristic offers amethod to potentially play a stronger positionalgame of chess. We conceptualize that an act(such as a move in a game) may be defined asa meaningful, intentional, purposeful effort onlyif it can be embedded within a story (Thiele,2006).

3 Principles of Positional Chess

Understanding the principles of positional chessis a necessary starting point before designingconcepts useful for a machine implementation.We select the relevant concepts of positionalchess which have been addressed by multiple au-thors.

(Stean, 2002) declares that the most impor-tant single feature of a chess position is the ac-tivity of the pieces and that the primary con-straint on a piece’s activity is the pawn struc-ture. (Znosko-Borovsky, 1980) generalizes thisprinciple by declaring that if two opposing piecesmutually attack each other, it is not the weakerbut the stronger one which has to give way. (Re-shevsky, 2002) notes that a good or bad bishopdepends on placement of the pawns. Piecesshould be ”working” and engaged, delivering thefull force of their potential and avoiding influ-ences which constrain. (Levy, 1976) discusses agame where a computer program accepts a posi-tion with an extra piece out of play, making a windifficult, if at all possible. Our evaluation shouldtherefore consider the degree to which a piece isin play or is capable of forcefully contributing tothe game.

Stean defines a weak pawn as one which can-not be protected by another pawn, therefore re-quiring support from its own pieces. This isthe ability to be protected by another pawn, notnecessarily the present existence of such protec-tion. Stean declares that the pawn structurehas a certain capacity for efficiently accommo-dating pieces and that exceeding that capacityhurts their ability to work together.

(Aagaard, 2003) declares that all positionalchess is related to the existence of weakness ineither player’s position. This weakness becomesreal when it is possible for the weakness to beattacked. The pieces on the board and theirconstraining interactions define how attackablethese weaknesses are.

(Emms, 2001) declares that is an advantageif a piece is performing several important func-tions at once, while a disadvantage if a piece isnot participating effectively in the game. Emms

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teaches that doubled pawns can be weak if theyare attackable or if they otherwise reduce themobility of the pawns. Doubled pawns can con-trol vital squares, which might also mean deny-ing mobility to enemy pieces. Isolated pawnsrequire the presence of pieces to defend them ifattacked.

(Dvoretsky and Yusupov, 1996) argue thatcreating multiple threats is a good starting pointfor forming a plan. Improving the performanceof the weakest piece is proposed as a good wayto improve your position as a whole.

(McDonald, 2006) gives an example of gooddoubled pawns which operate to restrict the mo-bility of the opponent’s pieces and are not easilyattackable. His view is that every position needsto be evaluated according to the unique featurespresent.

(Capablanca, 2002) and (Znosko-Borovsky,1980) speak of how the force of the chess piecesacts in space, over the chessboard, and throughtime, in sequential moves. Critical is the con-cept of position, which is valued by greater orlesser mobility plus the pressure exerted againstpoints on the board or against opponent’s pieces.Pre-eminence, according to Capablanca, shouldbe given to the element of position. We are alsoinstructed that the underlying principle of themiddle game is co-ordinating the action of ourpieces.

(Heisman, 1999) discusses the important el-ements of positional evaluation, including globalmobility of the pieces and flexibility.

(Albus and Meystel, 2001) have written thatthe key to building practical intelligent systemslies in our ability to focus attention on what isimportant and to ignore what is not. (Kaplan,1978) says that it is important to focus attention

on the few moves that are relevant and to spendlittle time on the rest.

The positional style is distinguished by po-sitional goals and an evaluation which rewardspieces for their future potential to accomplishobjectives. (Ulea, 2002) quotes Katsenelinboigenas saying that the goal of the positional style ofchess is the creation of a position which allowsfor development in the future. By selecting ap-propriate placement of pieces, combinations ide-ally will emerge. (Katsenelinboigen, 1992) fur-ther describes the organizational strategy of cre-ating flexible structures and the need to createpotential in adaptive systems that face an un-predictable environment.

(Botvinnik, 1984) and (Botvinnik, 1970) at-tempt in general terms to describe a vision forimplementing long range planning, noting thatattacking the paths that pieces take towards ob-jectives is a viable positional strategy. Positionalplay aims at changing or constraining the attackpaths that pieces take when moving towards ob-jectives - in effect, creating or mitigating stressin the position.

(Hubbard, 2007) identifies procedures whichcan be helpful when attempting to measure in-tangible values, such as the positional pressureproduced by chess pieces. (Spitzer, 2007) de-clares that what gets measured gets managed,that everything that should be measured, canbe measured, and that we should measure whatis most important.

The virtue of these example rules and prin-ciples (Thiele, 2006) arises not from their foun-dational status alone, but also from their rolewithin a narrative that outlines a developmentsequence. For Henry James ”Character is plot”(Thiele, 2006). The idea is that a writer first cre-ates strong characters, and the events that nat-

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urally follow as these characters interact drivethe plot. We suggest that ”Pieces and positionsare plot” - to forecast how the plot develops onthe gameboard (given the position of the piecesat hand) is our practical task. We agree with(Thiele, 2006) that practical judgment cannotbe distilled into algorithms alone. It is bothreliant upon (alternative) narratives in its for-mation and, retrospectively, is best explained byway of narratives. In effect, practical judgmentis grounded in narrative. More on this later. Itis also grounded in virtues which enable us toovercome the harms, dangers, temptations anddistractions which might otherwise prevent ourstrategic efforts from obtaining practical results(MacIntyre, 2007).

4 Systems Engineering

A system (Kossiakoff and Sweet, 2003) is a setof interrelated components working together to-ward a common objective. A complex engineeredsystem is composed of a large number of intri-cately interrelated diverse elements. von Berta-lanffy is of the opinion (von Bertalanffy, 1968)that the concept of a system is not limited tomaterial entities but can be applied to any wholeconsisting of interacting components. This de-scription could also apply to the situation facedby an agent playing a game, where the piecesrepresent the interrelated diverse elements. vonBertalanffy further identifies dynamic interac-tion as the central problem in all fields of reality(which would include playing a game), identi-fying system elements in mutual interaction asthe very core issue. Additionally, we are told tosuspect systems or certain systems conditions atwork whenever we come across something thatappears vitalistic or human-like in attribution.

We therefore see an opportunity to apply prin-ciples of System Theory, and in particular, Sys-tems Engineering, to game theory.

How would we begin? We now apply basicprinciples of Systems Engineering from (Kossi-akoff and Sweet, 2003):

A needs analysis phase defines the need fora new system. We ask ”Is there a valid needfor a new system?” and ”Is there a practical ap-proach to satisfying such a need?” Critically, canwe modify existing designs, and is available tech-nology mature enough to support the desiredcapability? The valid need would be to playa stronger positional game of chess, and exist-ing technology has struggled with the conceptof positional chess, as reflected in recent corre-spondence games which use Shannon-based pro-grams. It would seem that we need a differentapproach, which might be as simple as attempt-ing to emulate the style of play performed bystrong human players.

The concept exploration phase examines po-tential system concepts in answering the ques-tions: ”What performance is required of the newsystem to meet the perceived need?” and ”Isthere at least one feasible approach to achiev-ing such performance at an affordable cost?” Wewould answer the first question as simply thatour software function as an adequate analysistool, capable of selecting high-quality positionalmoves (with quality of move proportional to theanalysis time spent) when left ”on” for indefi-nite periods of time. As far as the second ques-tion, we might speculate that a new approachis needed, which feasibly we could model afterhumans playing the game.

The concept definition phase selects the pre-ferred concept. It answers the question: ”Whatare the key characteristics of a system concept

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that would achieve the most beneficial balancebetween capability, operational life, and cost?”To answer this question a number of alterna-tive concepts might be considered and their rel-ative performance, operational utility, develop-ment risk, and cost might be compared. The firstconcept we might consider would be the Shannonapproach, which has been the backbone of mostsoftware computer chess programs. We presentin this paper, defined in another section, anotherapproach. We therefore decide to explore theconcept definition phase in more detail, as welook for key system characteristics which con-ceptually could serve as the base of such a newsystem.

5 Systems Thinking

The heart of Systems thinking, whichis different from analytical thinking, isthe attempt to simplify complexity.

Systems thinking is a discipline for observ-ing wholes (Senge, 2006). It is a framework forobserving interrelationships rather than things,for observing the effects of change rather thanstatic snapshots. The heart of Systems think-ing, which is different from analytical thinking,is the attempt to simplify complexity (Ghara-jedaghi, 2006). We see an opportunity to ap-ply principles of Systems thinking to game the-ory. (Gharajedaghi, 2006) discusses how inde-pendent variables are the essence of analyticalthinking. We might find, on closer inspection,that our independent variables are not truly in-dependent - that the whole is more than a sim-ple sum of the parts. Emergent properties of asystem are a product of interactions and can-not (Gharajedaghi, 2006) be analyzed or ma-

nipulated by analytical tools, and do not havecausal explanations. We must instead attemptto understand the processes that produce themby managing the critical interactions. One mightthink of emergent properties as being in the pro-cess of unfolding. What makes it possible to turnthe systems approach into a scientific approachis our belief that there is such a thing as approx-imate knowledge (Capra, 1988). Systems think-ing also shows that small, well-focused actionscan produce significant, enduring improvements,if they are in the right place (de Wit and Mayer,2010). Systems thinkers refer to this idea as theprinciple of leverage. Tackling a difficult prob-lem is often a matter of seeing where the leveragelies, where a change - with a minimum of effort- would lead to lasting, significant improvement(de Wit and Mayer, 2010).

(Gharajedaghi, 2006) informs us that un-derstanding consequences of actions (both short-and long-term, in their entirety), requires build-ing a dynamic model to simulate the multiple-loop, nonlinear nature of the system. Our modelshould aim to capture the important delays andrelevant interactions among the major variables,but need not be complicated.

We therefore attempt to approach the orien-tation/evaluation methodology from a Systemsperspective. We will look at the interactions ofthe pieces and their ability to create and miti-gate stress. We adopt constraints, vulnerability,dynamic modeling, and resiliency as higher levelconcepts which will help cut through the com-plexity and steer diagnostic exploration effortsalong the lines of the most promising moves. Thetechnique of modeling (Kossiakoff and Sweet,2003) is one of the basic tools of systems engi-neering, especially in situations where complex-ity and emergence obscure the basic facts in a

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situation.

From (Anderson and Johnson, 1997), we ap-ply Systems thinking to look at the web of in-terconnected, circular relationships present in achess position, confident that this is the propertool for doing so. Our reason for believing thisis that everything in a chess position is (An-derson and Johnson, 1997) dynamic, complex,and interdependent. Things are changing all thetime, analysis is messy, and the interactions ofthe pieces are all interconnected.

we apply Systems thinking to lookat the web of interconnected, circularrelationships present in a chess posi-tion, confident that this is the propertool for doing so.

As we attempt to construct resilient gamepositions, we follow (Tierney and Bruneau, 2007)and identify 4 system level components of re-siliency: Robustness - the ability of our game-playing agent to withstand our opponent’s forceswithout degradation or loss of performance; Re-dundancy - the extent to which pieces, structuresor moves are substitutable, that is, capable ofsustaining operations, if degradation or a sur-prise move occurs; Resourcefulness - the abilityof our agent to diagnose and prioritize candidatemoves and to initiate solutions by identifying andmobilizing appropriate amounts of diagnostic ex-ploration time and game resources; and Rapidity- the capacity to restore or sustain functionalityin a timely way, containing losses by graceful fail-ure and avoiding other disruptions.

6 Goldratt’s Theory of Con-straints and Thinking Pro-cess

Goldratt (Goldratt and Cox, 2004) has devel-oped a Theory of Constraints which postulatesthat organizations and complex systems are hin-dered from reaching their goals by the con-straints placed on that system. Identifyingthose constraints and removing them can speedprogress towards these goals. (Scheinkopf, 1999)describes how Golratt’s institute began to mod-ify the original concepts to serve the needs ofclients who wanted more generalized proceduresto solve a wider variety of problems outside of afactory production environment.

Goldratt’s ideas, while seemingly original,can be properly classified as a Systems thinkingmethodolgy which emphasizes raw human think-ing over the construction and implementationof computer models. Each approach is useful.Also emphasized is a vocabulary and terminol-ogy which allows groups to construct and discussanalytical diagrams of feedback loops and iden-tify root causes.

Constraints shape and focus prob-lems and provide clear challenges toovercome. -Marissa Mayer

(Dettmer, 2007) explores Goldratt’s Think-ing Process and identifies procedures to logicallyidentify and eliminate undesirable effects fromsystems and organizations.

(Dechter, 2003) explains that a model of re-ality based on constraints helps us to achieve aneffective focus for diagnostic exploration efforts,and is similar to the heuristic process that hu-mans use to obtain effective solutions in com-plex situations. Removing the constraints par-

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tially solves the problem, and measured progresstowards removing these constraints can orient di-agnostic exploration efforts when identifying po-sitions and lines of analysis which are promising.

The realities are these con-straints... we turn those constraintsinto action -Frank Gehry

(Hollnagel et al., 2006) speak of identifyingand monitoring the ”barriers” which keep thesystem response within safe margins. Also, theuse of ”audit tools” is envisioned as a method tomeasure the effectiveness of the containment.

7 Soft Systems Methodology

(Checkland and Poulter, 2006) present a modi-fied Systems methodology where complexity andconfusion are tackled through organized explo-ration and learning. We envision the continuouschange present in the game of chess as a complexstate that needs to be (at least partially) under-stood in order to make exploration efforts (of anexponentially growing tree) more efficient.

what we really need is an insightfuland informed direction for explorationand a notion for how pressing this di-rection becomes strategically.

We conceptualize a learning agent whichgathers relevant information as it seeks to de-termine the cumulative stress present in the po-sition, in order to determine the paths of ex-ploration - the ones of promise and the onesof risk mitigation. Our Systems model (makingup our orientation/evaluation methodology) willideally suggest to us what moves are promising

or worth our time exploring, as well as to rec-ommend which paths can, justifiably, wait untillater. The heuristics which make up this learn-ing and decision making process will be discussedin a later section. Critical to these heuristics isthe concept that all dynamic behavior emergesfrom a combination of reinforcing and balancingfeedback loops (Anderson and Johnson, 1997).

Curiously, our orientation/ evaluation ’func-tion’ will become a methodolgy rather than aformula. We share Botvinnik’s puzzlement withan evaluation ”number” (Botvinnik, 1970) whenwhat we really need is an insightful and informeddirection for exploration (orientation) and a no-tion for how pressing this direction becomesstrategically.

The insight we obtain by this method is usedas a spring for action (Checkland and Poulter,2006), as our software agent decides what to donext, after completing the current evaluation.Our ”evaluation” ideally produces candidate di-rections for exploration, as part of a carefullyconstructed strategic plan, and indicates whichpaths are critical and which can wait until later.For Checkland, our model is an intellectual de-vice we use to richly explore the future, usingstress transformation as our chosen strategy, orworldview. Simply put, our model tells us whichpaths to explore.

Our estimate of the winning chances of acandidate position critically depends on the iden-tification and exploration of the critical candi-date sequences of moves, and the correct classifi-cation of the worthiness (for timely exploration)of such candidate positions. A heuristic estimateof the cumulative stress present in the position,at the end of our principal variation, can be cor-related, if desired, with winning chances. How-ever, our operational use of this value is for (cy-

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bernetically) steering diagnostic exploration ef-forts.

8 Measurement

Measurement plays a dual role (DiPiazza and Ec-cles, 2002): it focuses attention on what is impor-tant, as determined by strategy, and it monitorsthe level of performance along those dimensionsin the effort to turn strategy into results. Cer-tain measures can be predictive in nature, andwe aim for successful use of those measures asa management tool in steering diagnostic explo-ration efforts.

Measurement systems create the basis foreffective management, since you get what youmeasure. Management therefore needs to focusits attention on the measures that really drivethe performance or success they seek (Spitzer,2007). Spitzer also speaks about the criticalneed to develop metrics which are predictive andwhich measure strategic potential. We seek tomeasure how ”ready” our pieces are (and thestructures they form) for supporting strategy(Kaplan and Norton, 2004), especially when thefuture positions we face are not entirely deter-minable. An asset (such as a game piece) thatcannot support strategy has limited value. Partof our orientation/evaluation of the promise of aposition should ideally include the readiness ofthe pieces and structures to support future de-velopments. We embrace the principle that whatyou look for is what you find.

For (Zeller and Carmines, 1980), measure-ment clarifies our theoretical thinking and linksthe conceptual with the observable. For mea-surement to be effective, we must first constructa valid sensor. In our attempts at measurement,

we seek empirical indicators which are valid, op-erational indicators of our theoretical concepts.We desire to construct a diagnostic indicatorwhich gives, as a result, a useful predictive mea-sure of future promise and a direction for futureexploration.

Although it would seem that a perceptionbased on simplicity would yield the best all-around results, (Blalock, 1982) points out thedifficulties trying to simultaneously achieve sim-plicity, generality, and precision in our measure-ment. If we have to give up one of these three, itis Blalock’s opinion that parsimony, or the scien-tific idea that the simplest explanation of a phe-nomenon is the best one, would have to be sac-rificed in order to achieve the other two. Laszlo(Laszlo, 1996) suggests that science must bewareof rejecting the complexity of structure for thesake of simplicity. Therefore, our attempts to de-scribe a complex orientation/evaluation method-ology are grounded in the two-fold goals of gen-erality (it must be applied to all positions weencounter) and precision (otherwise, diagnosticexploration efforts are wasted on less promisinglines).

Essentially, oversimplifying complex prob-lems is dangerous and can mislead an analyst tooffer a detrimental judgment (Fleisher and Ben-soussan, 2007). Parsimony is a virtue for the-orists, but a vice for storytellers (Thiele, 2006)- the rich detail of narrative provides judgmentits key resource. Narrative is not forged fromthinly articulated generalities, but from the thickdescription of specific circumstances that housedistinctly specific opportunities and obstacles(Thiele, 2006). Starbuck and Milliken’s refer-ence to ”perceivers who understand themselvesand their environments” reaffirms the impor-tance for sensemaking of complex sensors with

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sufficient variety to comprehend complex envi-ronments (Starbuck and Milliken, 1988) (Weick,1995). But while it is not naive or unreasonableto try to encompass most of another’s behaviorunder a very few rules, the more complete in-formation available later usually shows that thebehavior was the product of more numerous andcomplex forces than contemporary observers be-lieved (Jervis, 1976). And, more important fromour standpoint, the predictions that the highlyoversimplified model yields are often misleading(Jervis, 1976) - hindering our aim to develop asystem that will enable us to sense change earlierand respond to it more rapidly than our oppo-nent (Haeckel, 1999).

The alternative view is presented by (Gun-derson et al., 2010), who declare that experiencehas suggested to be as ruthlessly parsimoniousand economical as possible while still retainingresponsiveness to the management objectives andactions appropriate for the problem. Addition-ally, we are advised that the variables selectedfor system description must be the minimumthat will capture the system’s essential qualita-tive behavior in time and space. We are furthercautioned that the initial steps of bounding theproblem determine whether the abstract modelwill usefully represent that portion of reality rel-evant to policy design. We must therefore aimto simplify, but not so much as to impact theusefulness of the tool for predicting promisingpaths of exploration. We hypothesize that theuse of competition itself as an aid in constructingthe measurement model will allow complexity togrow as long as overall tournament performancedoes not decrease.

Perhaps what we should aim to minimizeinstead is the minimum of total information(Lloyd, 1995) - a learning process which min-

imizes total information can be shown (Lloyddeclares) to be the maximum likelihood model(Lloyd, 1995), the most concise and arguablymake the best possible prediction given data.

9 Vulnerability

Critical to the success of a computer chess pro-gram that attempts to play in the positional styleis the concept of vulnerability. The pieces andstructures that are or have the potential to be-come vulnerable will become a focus of our diag-nostic exploration efforts and will serve as targetsfor our long-range planning.

We follow (McCarthy et al., 2001) and con-ceptualize vulnerability as a function of expo-sure, sensitivity, and adaptive capacity. Conse-quently, the sensor we develop should attemptto measure exposure to threats, the sensitivityto the effects of stimuli, and the ability to adaptand cope with the consequences of change. Weenvision a sensor that produces a forecast of po-tential vulnerability as an output. This forecastcan guide exploration efforts by identifying tar-gets for the useful application of stress and serveas one indicator of a promising position.

Additionally, we predict that any machine-based attempt to zero-in on vulnerability thatdoes not address this conceptual base runs therisk of missing opportunities in exploring theexponentially growing tree of possibilities thatexist for each game position. A missed oppor-tunity might equally prevent us from increas-ing positional pressure on our opponent, or in-stead, might dissipate the pressure that we havecarefully accumulated over time. Our orienta-tion/evaluation of the winning chances presentin the position might not be as accurate as it

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could be unless we explore the promising posi-tions and consider the vulnerabilities that arepresent.

We conceptualize that the reduction of vul-nerability and the pursuit of sustainable develop-ment are interrelated aims (Smith et al., 2003).

10 Resilience

When something unexpected happens, it is re-silience we fall back on - resilience provides thecapacity to sustain strategy change (Valikangas,2010). Vulnerability is the condition that makesadaptation and resilience necessary as a mitiga-tion (Worldwatch, 2009). The scientific studyof resilience began in the 1970s when NormanGarmezy studied well-adapted children who hadovercome the stress of poverty (Lukey and Tepe,2008). Resilience is also an important researcharea in military science (Friedl, 2007) and in thestudy of ecosystems (Folke et al., 2002). We findthis concept useful in game theory.

In our view, adapted from (Luthar, 2003),resilience refers to an ongoing, dynamic devel-opmental process of strategically positioning re-sources that enables the player in a game to ne-gotiate current issues adaptively. It also pro-vides a foundation for dealing with subsequentchallenges, as well as recovering from reversalsof fortune.

We desire a generic, continuousability (both during crisis and non-crisis game situations) to cope withthe uncertain positions that arrivefrom beyond our planning horizon.

We desire a generic, continuous ability (bothduring crisis and non-crisis game situations) to

cope with the uncertain positions that arrivefrom beyond our planning horizon. Ideally, weseek to create a useful positional pressure to forcethese arriving positions to be in our favor, orminimally, to put a ”cage” of constraints aroundthe enemy pieces. Flexibility, adaptive capacity,and effective engagement of available resourceswill be our weapons against the dynamic changeswhich will unfold in our game (Hollnagel et al.,2008).

Ideally, we will look for and manage theheuristic early warning signs of a position ap-proaching a ”tipping point”, where a distinct,clear advantage for one side emerges from an un-clear array of concurrent piece interactions. Weagree with (Walsh, 2006) that resilience cannotbe captured as a snapshot at a moment in time,but rather is the result of an interactive processthat unfolds over time.

The failure to include resilience measure-ments like this in planning efforts might causea house-of-cards effect, as the weakest link inour plan might collapse, due to effects we cannotinitially perceive. This might create a situationfrom which we cannot recover, or from which wecannot continue to mount increasing positionalpressure on our opponent.

A central concept is the construction of aresilient position, one that ideally 1. possessesa capacity to bounce back from disruption inthe event of an unforeseen move by our oppo-nent, 2. produces advantageous moves in lightof small mistakes by our opponent, or 3. per-mits us to postpone our diagnostic explorationefforts at early points for less promising posi-tions, with greater confidence that we have suffi-cient resources to handle future unforeseen devel-opments if the actual game play proceeds downthat route. In simplest form, we might just mea-

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sure the ability to self-organize.When change occurs, the components that

make up resilience provide the necessary capac-ity to (minimally) counter and (ideally) seize newopportunities that emerge (Folke et al., 2002).Resilience is (minimally) insurance against thecollapse of a position and (ideally) an investmentthat pays dividends in the form of better posi-tions in the future. With no pun intended, wesee the struggle to control the unknown, emerg-ing future positions as a ”Red Queen’s Race”,where in tough-fought games against a talentedopponent, it might take all the effort possible tomaintain equal chances. Extraordinary effortsinvolving hundreds of hours of analysis per move(such as in correspondence games) might be re-quired to maneuver to an advantage (Jerz, 2007).

For (Reivich and Shatte, 2002), resilienceis the basic strength. (Hollnagel et al., 2006)suggest that ”incidents”, which for us might bethe construction of short sequences of just thetop few promising moves (diagnostic probing),might reveal insight to boundary conditions inwhich resilience is either causing the system tostretch to adapt, or buckle and fail. Emergencyresponse teams use practice incidents to measureresilience as unforeseen events emerge during op-erations. Fire drills, random audits and securitysearches, even surprise tests are diagnostic toolsused to detect and correct situations lacking inresilient capabilities.

We speculate that the ability toconstruct a resilient position and theability to perceive oriented stress in aposition are two primary conceptualdifferences between a game-playingman and machine.

We acknowledge the reality that our abilityto handle an unexpected move or critical situa-

tion in a game depends on the structures alreadyin place (Weick and Sutcliffe, 2007). We desire(Weick and Sutcliffe, 2007) to pay close attentionto weak signals of failure that are diagnostic in-dicators of potential problems in the system. Wealso perform diagnostic probing to uncover andsteer game play towards positions where thereare multiple good moves - an additional sign ofresilience.

We speculate that the ability to construct aresilient position and the ability to perceive ori-ented stress in a position are two primary con-ceptual differences between a game-playing manand machine. We believe that these abilities canbe emulated through the use of appropriate di-agnostic tests.

Humans construct resilient positions (instrategic situations) almost by instinct and of-ten without conscious thought (Fritz, 2003), indiverse situations such as driving automobiles,playing sports games, conducting warfare, socialinteraction, and managing resources in businessor work situations. Humans have such refinedabilities (Laszlo, 1996) to make predictions, in-terpret clues and manipulate their environment,that using them is frequently effortless, espe-cially if performed daily or over extended periodsof time. (Aldwin, 2007) points out that humansappear to be hard-wired physiologically to re-spond to their perceptions of stress - so much sothat effective responses can be generated contin-uously with little conscious thought. We there-fore see the machine-based perception of stressas critical to successful performance in a game.

Additionally, much has been written (Fagreand Charles, 2009) (Folke et al., 2002) concern-ing ecosystems, resilience, and adaptive manage-ment that has direct application to game theory.

Conceptually, we desire the equivalent of a

15


”mindset” that can successfully cope with prob-lems as they arise, as we attempt to 1. examinethe promising positions, 2. evaluate the corre-sponding winning potential and 3. orient ourdiagnostic exploration efforts through an expo-nentially growing ”tree” of strategically impor-tant move sequences. This process is aided bythe heuristic measurement of adaptive capacity,as the thousands of unexamined positions thatlie just beyond the point of our diagnostic ex-ploration cut-offs must be resilient enough tocounter whatever unknown events emerge. Be-fore we cut-off our diagnostic exploration ef-forts, we critically seek evidence of readiness,which depends on the perceived ability to quicklyadopt, adjust, or abandon initiatives and invest-ments once new conditions materialize (Beck-ham, 2002). Readiness describes an organizationthat can be viable across a variety of conditions(Beckham, 2002).

Rather than thinking about resilience as”bouncing back” from a shock or stress, it mightbe more useful to think about ”bouncing for-ward” to a position where shocks and stresseshave less effect on vulnerabilities (Walsh, 2006)(Worldwatch, 2009). Integral to the definitionof resilience are the interactions among risk andprotective factors (Verleye et al., prepub) at anagent and environmental level. Protective fac-tors operate to protect assets, such as pieces in agame, at risk from the effects of the risk factors.

We agree and conceptualize that, while riskfactors do not automatically lead to negativeoutcomes, their presence only exposes a game-playing agent to circumstances associated witha higher incidence of the outcome; protective ormitigating factors such as constraints can con-tribute to positive outcomes - perhaps regardlessof the risk status.

We accept as an operational concept of re-silience, the fourth proposal of Glantz and Slo-boda (Glantz and Johnson, 1999), which involvesthe adoption of a systems approach. We con-sider both positive and negative circumstancesand both influencing and protecting characteris-tics and the ways in which they interact in therelevant situations. Additionally, this conceptu-alization considers the cumulation of factors andthe influences of both nearby and distant forces.In addition, (Elias et al., 2006) discuss a model ofresilience in which specific protective influences(which we see as constraints) moderate the ef-fect of risk processes over time, in order to fosteradaptive outcomes.

We propose (Gunderson et al., 2010) an ap-proach based on resilience, which would empha-size the need to keep options open, the need toview events in a larger context, and the need toemphasize a capacity for having a large numberof structural variations. From this we recognizeour ignorance of, and the unexpectedness of fu-ture events. The resilience framework does notrequire a precise ability to predict the future, butonly a capacity to devise systems that can absorband accommodate future events in whatever un-expected form they may take. If we could cramMacGyver into our software, we would certainlydo so.

11 Inventive Problem Solving

Our chess program attempts to be, like Mac-Gyver, an inventive problem solver. We see ef-fective problem solving as an adaptive processthat unfolds based on the nature of the problem,rather than as a series of specific steps (Albrecht,2007). We agree with (Browne, 2002) that know-ing the difference between what’s important and

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what isn’t is a basic starting point.

We attempt to navigate an exponentiallygrowing tree of possible move sequences, select-ing those paths for exploration that are promis-ing, interesting, risk-mitigating, and resilient inthe face of an unknown future. We are concernedat all times with the potential of a position toserve as an advancing platform for future incre-mental progress towards positional goals (Fritz,2007). We will accomplish this by knowingthe outcomes we want and looking tirelessly forthem. (Savransky, 2000) lists three major re-quirements for a problem-solving methodology,which we modify slightly for the purposes of amachine playing a game:

1. It should focus on the most appropriateand strongest solutions

2. It should produce, as an output, the mostpromising strategies

3. It should acquire and use important, well-organized, and necessary information at all stepsof the process

(Savransky, 2000) additionally suggests thatwe should focus on gathering the important in-formation, information which characterizes theproblem and makes it clear, including contra-dictions. Any simplifications we perform shouldaim at reducing the problem to its essence andbe directed towards our conceptual, strategic so-lution.

As an example, typical American news re-ports each day announce the results of the DowJones index of stocks. This weighted index of30 representative companies serves as a good in-dicator of overall market performance and canhelp answer the question ”How did the marketsdo today?”. To obtain this numerical value, youjust sum the prices of each of the 30 specific com-

panies and divide by a number which takes intoaccount stock splits and stock dividends.

We seek an equivalent summary numericalrepresentation of reality (March, 1994) which canserve as a guiding light and a measure of progresstowards our distant positional goals. We are notrestricted to the use of a single scoring metric,and can combine multiple, critical metrics in cre-ative ways, including the selection of the lowestscore from several indicators to provide a diag-nostic exploration focus. We should first form aconcept of what should be measured, then cre-ate a sensor array which allows us to measureand perform diagnostic exploration efforts (in anexponentially growing tree of possible continua-tions) with reasonable efficiency.

12 Strategy and the StrategicPlan

I do not claim that strategy is or canbe a ”science” in the sense of thephysical sciences. It can and should bean intellectual discipline of the highestorder, and the strategist should pre-pare himself to manage ideas with pre-cision and clarity and imagination...

The core of strategy work is always the same:discovering the critical factors in a situation anddesigning a way of coordinating and focusing ac-tions to deal with those factors (Rumelt, 2011).A good strategy honestly acknowledges the chal-lenges being faced and provides an approach toovercoming them (Rumelt, 2011). Strategy isabout action, about doing something. The coor-dination of action provides the most basic sourceof leverage or advantage available in strategy

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(Rumelt, 2011). A new strategy is, in the lan-guage of science, a hypothesis, and its implemen-tation is an experiment. Practically, our hypoth-esis is built on functional knowledge about whatworks, what doesn’t, and why (Rumelt, 2011).

...Thus, while strategy itself maynot be a science, strategic judgmentcan be scientific to the extent that it isorderly, rational, objective, inclusive,discriminatory, and perceptive. -J.C.Wylie

We follow Beckham (Beckham, 2000) andWylie (Wylie and Wylie, 1989) and define strat-egy as a plan for using leverage to get from apoint in the present to some point in the futurein the face of uncertainty and resistance. Weconcur that without a future that involves someuncertainty and resistance, there is no need fora strategy. A strategy has lasting power - itseffects are sustained over a time horizon (Beck-ham, 2000). Strategy is a kind of investment inthat it aims to create or sustain significant value.Strategy deals with the important in a way thatis deemed necessary for sustainable success.

Leverage is critical for Senge (Senge, 1990),as the leverage in most management situationslies in understanding dynamic complexity, notdetail complexity. Dynamic complexity ariseswhen cause and effect are distant in time andspace, and when the consequences over time ofinterventions are subtle and not obvious.

More specifically, Rumelt (Rumelt, 2011)declares that a strategy is a coherent set of anal-yses, concepts, policies, arguments, and actionsthat respond to a high-stakes challenge. ForRumelt, the kernel of a strategy contains threeelements: a diagnosis, a guiding policy, and co-herent action. A strategy is a way through a dif-

ficulty, an approach to overcoming an obstacle,a response to a challenge. If the challenge is notdefined, it is difficult or impossible to assess thequality of the strategy (Rumelt, 2011). A goodstrategy doesn’t just draw on existing strength;it creates strength through the coherence of itsdesign. The most basic idea of strategy is the ap-plication of strength against weakness (Rumelt,2011).

The only kind of strategy thatmakes sense in the face of unpre-dictable change is a strategy to becomeadaptive.... when change becomes un-predictable, it follows that the appro-priate response will be equally so. Inthis environment, therefore, plannedresponses do not work. -StephanHaeckel

Anyone or anything lacking a strategy isundertaking a journey without a map. Its ac-tions will be an incoherent series of ad hocand perhaps mutually conflicting responses tonew events (Murphy, 2005). A competing en-tity’s competitive capability depends upon theresources at its disposal and how efficiently theyare used. Winners need to combine a soundstrategy with a fitting level of resources - theymust also correctly identify the critical successfactors for the environment in which they chooseto compete (Murphy, 2005). A strategy deliverssignificant improvements in the key indicators ofsuccess (Beckham, 2000). We need to get into aloop linking action, perception and thinking to-wards continual learning. An effective strategy isone that triggers our successful launch into thatlearning loop (van der Heijden, 2005). From ascenario planning point of view, the best strat-egy is the one that gives the organization thegreatest degree of flexibility. As the future takes

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shape (whichever future it happens to be), wewill want room to maneuver (Wade, 2012).

We see a strategic plan (Bradford et al.,2000) as a simple statement of the few thingswe really need to focus on to bring us success,as we define it. It will help us manage everydetail of the game-playing process, but shouldnot be excessively detailed. It will encapsulateour vision and will help us make decisions as wecritically choose, or choose not, to explore futurepositions in our diagnostic exploration tree. Wesee the formation and execution of the strategicplan as the most effective way to get nearer to thegoal state, especially in a competitive environ-ment where our opponent is also attempting todo the same. The simple principles that governstrategy are not chains but flexible guides leav-ing free play, in situations that are themselvesenormously variable (Castex and Kiesling, 1994).Wylie’s general theory of strategy, applicable inany conflict situation, is a worthwhile startingpoint and overall guide (Wylie and Wylie, 1989).

We see the role of the machine asmerely that of an executor of a strate-gic plan... we simply ask the machineto do what it is told.

We see the role of the machine (in playinga game such as chess) as merely that of an ex-ecutor of a strategic plan, where we have previ-ously defined (through programmed software in-structions) the specific answers to the questions”Where do we want to be?” ”How will we knowwe have reached it?” ”What is changing in theenvironment that we need to consider?” ”Whereare we right now?” and ”How do we get from hereto our desired place?” (Haines, 1998). In our vi-sion, the intelligence is located in the strategicanswers to these questions and in the skill of the

programmer in implementing them - we simplyask the machine to do what it is told. We bor-row a cleverism from Foucault and declare thatthe machine ”cares” about what it does - mostlyloading, storing, adding, comparing, branching,and logical operations on chunks of data on com-mand - it just does not ”care” (or understand)what what it does does.

computers... cannot understandsymbols (or indeed anything else ei-ther), though they can manipulatesymbols according to formal rules withconsummate speed and accuracy, farsurpassing our own fumbling efforts...they do not understand the questionsthey are asked or the answers theyprovide. - Richard Gregory

If one game-playing computer program isbetter than another, as demonstrated in a tour-nament of many games played, we speculate thatthe reason is either a better strategic plan ora better software implementation of that plan.Therefore, improvements in computer chess pro-grams ideally should focus on these two areas,including answers to the questions presentedabove. For Haines, all types of problems andsituations (which include selecting a move in agame) can benefit from a strategic approach.

Before we develop our strategic plan, weask ourselves and ponder three critical questions(Jorgensen and Fath, 2007): 1. what are theunderlying properties that can explain the re-sponses we see on the game board to pertur-bations and interventions, 2. are we able toformulate at least building blocks of a manage-ment theory in the form of useful propositionsabout processes and properties, and 3. can weform a theory to understand the playing of chess

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that is sufficiently developed to be able to ex-plain observations in a practical way for choos-ing a move? We do not see the need to con-struct mathematical proofs - the concepts of use-ful propositions and effective strategic principlesallow us flexibility in choosing an approach andallow us to consider multiple options before set-tling on one with the most promise. We return tothese critical questions whenever we seek direc-tion or clarification in an approach, or considerstarting over. We look to other disciplines - assuggested by (Boyd, 1987) - and to other pro-fessionals who have sought answers to the samequestions, which must be asked in a general wayto any management problem.

Central to our strategic plan are the follow-ing concepts (Jorgensen and Fath, 2007): systembehavior frequently arises out of indirect inter-actions that are difficult to incorporate into con-nected models, that we may not know exactlywhat happens, but approximately what happens,and that we can use holistic metrics to measurethe growth and development of a position in agame.

A vision involves... ”anticipativeshaping” that seeks to discern not onlythe powerful currents of the future butalso how those currents can be lever-aged... it’s foolhardy to assume youcan control the future... The futurewill consist of powerful flows that, likethe weather, can be leveraged and rid-den but can never be controlled...

We acknowledge that systems have a com-plex response to disturbances, and that con-straints play a major role in interactions. Asa strategy we seek a method to determine (andto resolve uncertainty concerning) 1. the promis-ing candidate moves in a given position, and 2.

the chances of sustainable development in a po-sition, allowing us to postpone (if necessary) theexploration of future consequences.

...Trips to the future begin with astruggle to see and understand thesepowerful currents: their general direc-tion, their power, and where they maycollide and coalesce. - J. Daniel Beck-ham

In a building block for our strategic plan,we examine the position under inspection for thepresence of stressors (Glantz and Johnson, 1999)and determine their contribution to the cumula-tive stress in the position. A stressor is a realobject on the game board, such as a piece, oran object or property that might become realin the future, such as a Queen from a promotedpawn, a stone in the game of Go, or a King in thegame of draughts/checkers. Using our stressors,we seek to establish a structural tension (Fritz,1989) that, if resolved, leads to positions thatfavor us.

In a building block for our strategicplan, we examine the position underinspection for the presence of stres-sors... We attempt to cope with thestressors of our opponent by weaken-ing them or reducing their influenceto a manageable level

The stress we seek to place on our oppo-nent (Glantz and Johnson, 1999) is the kind thatinterferes with or diminishes the developmentof our opponent’s coping repertoire, diagnosticexploration and planning abilities, expectationsand potential resilience. This stress is ideally soeffective that we create a platform from which wecan apply even more stress. We force our oppo-nent to divert additional resources to containing

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our threats, making fewer resources available forthreats of his own.

We attempt to cope with the stressors of ouropponent by weakening them or reducing theirinfluence to a manageable level (Snyder, 2001)- there is no compelling need to make their ef-fects go away completely. For (von Bertalanffy,1968), stress is a danger to be controlled andneutralized by adaptive mechanisms. We gatherdiagnostic information that is used to determinethe readiness of the pieces to inflict stress on theopponent and lessen the stress imposed by theenemy pieces on our weak points. The creationof effective stress and the perceived mobilizationof forces to mitigate it will become a central con-cept in our orientation/evaluation.

Our orientation/evaluation looks not somuch to goal seeking/optimizing a ”score” asto sustaining relationships between/among thepieces and learning what happens as stress ismoved from one area of the board to another.What is relevant cannot be known until later.The kinds of predictions we most want to make,we feel, require us to first determine which of allthe things that might happen in the future willturn out to be relevant, in order that we can startpaying attention to them now (Watts, 2011). Weacknowledge openly (Watts, 2011) that there arelimits to what can be predicted - we thereforeseek to develop methods for planning that re-spect those limits.

Figure 1: Simplified model (dynamic hypothesis) of posi-tional pressure for each piece

Figure 1 shows a simplification of the pro-posed model of positional pressure for each piece,based on principles of system dynamics. Thefuture mobility of each piece targets opponentpieces, the trajectories taken by these pieces, andcertain other weaknesses such as weak pawns,the opponent’s king, or undefended pieces. Thisthreat is mitigated (but not reduced completely)by the protective factor of constraints imposedby the lower-valued enemy pieces. The resid-ual ”Stock” is the effective stress that can befelt by our opponent, and which we seek to in-crease. For (Warren, 2008), the management ofcritical resources is part of an emerging theory ofperformance: performance depends on resourcecontribution, resource contribution accumulatesand depletes, and this depends on existing re-source contribution levels.

Figure 2 shows the plan for managing theperceived stress by incentivizing a coping strat-egy, such as the placement of constraints, in or-der to control the effects of the overall cumulativestress. We seek to maintain a resilient positionfull of adaptive capacity.

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Figure 2: As perceived stress increases, we increase the in-centive to cope with the stress

Things start to get complicated when we re-move stress (and the associated constraints) fromone area of the board and apply it to other areas.The short- and long-term effects of these stress-exchanging maneuvers are examined through ori-ented and prioritized diagnostic exploration ef-forts, and in our opinion represent the essence ofplaying a game such as chess. This conceptualmodel will form the basis of the machine’s per-ception. We rely on the simplifying principles ofsystem dynamics to predict and anticipate theeffects of such stress transformation.

From (Friedl, 2007) we define a stressor asany challenge to a player in a game that evokesa response. Coping is the set of responses thatsustain performance in the presence of stressors.Resilience is the relative assessment of copingability. We desire to create in our opponent’sposition a condition similar to fatigue, definedby Friedl (and modified for game theory) as thestate of reduced performance capability due tothe inability to continue to cope with stressors.We follow Fontana (Fontana, 1989) and define

stress as a demand made upon the adaptive ca-pacity of a player in a game by the other. Wetheorize a correlation between the state of stress-induced reduced performance capability and an”advantage”, or favorable chances for the morecapable player winning the game.

we are dealing with a processwhose effects take time in revealingthemselves

Strategically, we seek to identify the stresspresent in the position by 1. examining the de-mands of each stressor, 2. the capacity of eachplayer to respond to those demands, and 3. theconsequences of not responding to the demands.

we will predict the winning chancesat some future point in time, af-ter the present circumstances progressand the structures in place are allowedto unfold

We carefully define weakness so that thestress and tension we create is focused and ef-fective. The information we gather from the in-teracting pieces should be precise enough to getresults - it does not need to be perfectly accurate.Information is power (Bradford et al., 2000), es-pecially in strategic planning. Along the way, wewill need to make assumptions about whether ornot the stress we are inflicting on our opponent isincreasing or decreasing, and whether it is effec-tive or not effective. We might explore promis-ing paths in detail to confirm our assumptions,or we might just rely on our measurements ofresilience.

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Figure 3: Conceptual Framework, from Chapin, 2009, p.21

Critical is our ability to orient our diagnos-tic exploration efforts on lines that are promis-ing, with regard to the oriented application ofstress and the predicted effects on future lines ofplay. In our opinion (Schumpeter, 2008), we aredealing with a process whose effects take time inrevealing themselves - we will predict the win-ning chances at some future point in time, af-ter the present circumstances progress and thestructures in place are allowed to unfold, includ-ing the newly emergent features which we arenot currently able to perceive. We establish aportfolio of promising lines, and see where theygo. We invest our time and processor resourcesin the most promising, but only after investigat-ing the promising via a swarm of lower-risk ex-periments (Hamel and Valikangas, 2003). Wedefine a concept of stress which lets us orientour diagnostic exploration efforts on anticipatedpromising lines. We rely on the promise of adap-tive capacity present in resilient positions to sus-tain our efforts in lines where the perception ofweaker cumulative stress, time constraints, andour model of purposeful activity do not permitus to explore.

We theorize that the dynamic forces ofchange during the playing of a game have anadaptation cost associated with them (Kelly andHoopes, 2004) (Zeidner and Endler, 1996). Thismight come from a shift in expectations, or froma required recovery from disruptions. We make”payments” for these adaptation costs from our”bank” of resilience. If we lose our positional re-silience, we lose our flexible ability to adapt tothe unknown requirements of change. Likewise,we can make ”deposits” to our resilience accountduring quiet periods of maneuver, if we choose,and if we value resilience as an element of our ori-entation/evaluation methodology. Friedl (Friedl,2007) refers to this concept as pre-habilitation.We seek to attack our opponent’s capacity to re-spond and to strengthen our own, so that thedynamic forces of change that drive the gamecontinuation will cause the unknown positionsarriving from beyond our planning horizon to bein our favor.

We seek a resilient mindset. Specifically, wefollow Coutu (Coutu, 2003) and aim for threefundamental characteristics: we identify and facethe reality of the stresses and constraints presentin the positions we evaluate, we identify and re-ward the values of positional chess, and we de-velop an ability to improvise solutions based onwhatever resources are available to us. We seekto prepare for an unknown future that can be in-fluenced by the strategic placement of resourcesin the present.

A strategic thinker never allowshimself to lose sight of the key fac-tors... he will shape his strategy - astrategy not for total war on all frontsbut for a limited war on the fronts de-fined by the key factors for success...it is this focus on key factors that

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gives the major direction or orienta-tion to the operation we call strategicthinking -Kenichi Ohmae

In the generalized exchange of pieces,squares, and opportunities encountered in gameplaying (Botvinnik, 1970), we seek to establisha pressure that has a realistic chance to resolvein our favor, as determined by heuristic probingand the examination of promising future gamesequences. We desire to create and sustain aweb of stress which threatens to become real andtherefore has the property that (von Neumannand Morgenstern, 1953) have called ”virtual” ex-istence. Our opponent must ”spend” or dedi-cate resources to contain or adapt to the threats.Even if a particular threat is contained, it never-theless has participated in the dynamic shapingand influencing of the events that emerge andunfold in the game.

We will succeed at forming an effectivestrategic plan when we have identified our values,determined the key drivers to performance, de-veloped a sensor which is effective at measuringthem, and have focused on the lines of play thatare promising. At all times we wish to maintaina resilient position, which increases our ability toeffectively handle the unknown positions whichlie beyond the horizon of our explorations.

We will use two key strategies (Maddi andKhoshaba, 2005) to become and remain resilient:we will develop the vision to perceive changes inthe promise of a position (as they emerge fromour heuristic explorations), and we seek flexi-bility to act quickly, while remaining focusedon our goals of establishing and maintaining auseful structural tension. We seek (Kelly andHoopes, 2004) a balanced portfolio of resilienceskills, where ideally we are focused, flexible, or-ganized, and proactive in any given situation.

We believe that resilient responses (Kelly andHoopes, 2004) are the result of resilience char-acteristics operating as a system, as we evaluateand predict the emergent results of change.

Following Jackson (Jackson, 2003), we avoidplacing a complete reliance on specific predic-tions of the future, concentrating on relation-ships, dynamism and unpredictability as much aswe do on determinism. In our plan, we will adaptas necessary and seize new opportunities as theyemerge from the ”mess”. We seek to focus onidentifying and managing the structures that willdrive the behavior of the game, and acknowledgethe reality that large portions of the future pos-sibilities will go unsearched and unexplored (un-til they emerge from beyond our planning hori-zon and into our perception). As we deepen ourexploration and learning, we see new opportu-nities emerging as much for us as for our oppo-nent, and requiring us to re-direct our diagnosticexploration (and planning) efforts. We see thewidest possible spectrum of adaptive responsescompeting for the fittest solution (Bossel, 1998).Diversity is an important prerequisite for sus-tainability.

Where possible, we follow the advice ofFrench military strategist Pierre-Joseph Bourcet(Alexander, 2002) and spread out attackingforces over multiple objectives, forcing an ad-versary to divide his strength and prevent con-centration. Such divided forces - a ”plan withbranches”, can be concentrated at will, espe-cially if superior mobility is present, as recom-mended by French military strategist Guibert.As an end result of all this positional pressureand maneuver, we seek what Napoleon sought,that is (Alexander, 2002), the nature of strategyconsists of always having (even with a weakerarmy) more forces at the point of attack or at

24


the point where one is being attacked than theenemy. Such positions have the possibility of thewin of material, and are then approached froma more tactical perspective - one that currentheuristics handle well.

From a high level, we visualize the oppo-nent’s pieces in the game of chess as a network,and agree with Wilson (Wilson, 2006) that thebest way to confront a network is to create acounternetwork, a non-hierarchical organizationcapable of responding quickly to actionable in-telligence obtained from diagnostic efforts. Net-works are an essential ingredient in any complexadaptive system. Without interactions betweenagents, there can be no complexity (Beinhocker,2007).

We aim for control (Wylie and Wylie, 1989)(Kelly and Brennan, 2010), defined by Mc-Cormick (McCormick, 2005) as (1) the abilityto see everything in one’s area of operation thatmight pose a threat to security and (2) the abilityto influence what is seen. Our main efforts mustbe to establish dynamic control. Once control isestablished, the opponent becomes an ineffectivefighting force - but only in the way a tiger be-comes contained within the cage. Direct actiondoes not provide control; control provides theability to conduct effective direct action (Canon-ico, 2004). More specifically, we seek to managethe leverage in dislocating the enemy (Wylie andWylie, 1989) (Palazzo et al., 2010) that leads tocontrol, and to face up to the questions surround-ing how influence and the threat of destructionlead (dynamically, now or later) to the controlwe seek.

We strategize with Schoemer (Schoemer,2009) that our success depends on changingquickly and effectively so that we can do whatneeds to be done in the future. Change is un-

predictable - we can’t know which changes willoccur, so our most valuable skill is being able tomaster any changes that do. We need to learnhow to master the inevitable, yet unpredictable,change we will face in playing our game. Weseek to control the controllables - learning howto focus our time and energy on issues where wecan make a difference and learning how not towaste our time and energy on problems we can’tsolve. We theorize with Schoemer that misman-aged change leaves us worse off than before, andresults in even more change. We identify thosethings that we can control and then get busycontrolling them (Schoemer, 2009).

We see the indirect approach as the most di-rect path to victory (Wilson, 2006) (Hart, 1991).

We cannot improve on the centuries-old ob-servation that the secret of all victory lies in theorganization of the non-obvious (Marcus Aure-lius). To accomplish this, we follow (Maslow,1987) and critically focus our attention on theunusual, the unfamiliar, the dangerous and thethreatening, while seeking (from necessity, andfor exploration purposes) to separate the dan-gerous positions from the safe.

We desire to create, in the words of Vickers(Allison and Zelikow, 1999) (Vickers, 1995), anappreciative system, where our value judgmentsinfluence what aspects of reality we care to ob-serve, which in turn are influenced by instrumen-tal calculations, since what we want is affected bywhat we think we can get. We seek to establisha readiness to distinguish and respond to someaspects of a system rather than others, and tovalue certain conditions over others. Central tothis concept will be indicators which aim to mea-sure cause rather than effect, and the gatheringof early knowledge as the essence of preparation(Beckham, 2007). If our chess playing agent can

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successfully act as a rational actor, it is throughthe mechanism of an appreciative system thatthis is accomplished.

13 Competitive IntelligenceLeads to Competitive Ad-vantage

We see one factor above all others as contribut-ing to the success (or failure) of the proposedheuristic: the gathering of useful competitive in-telligence. Very simply, competitive intelligenceis any information that tells us whether our posi-tion is still competitive, or how to make it morecompetitive (Gilad, 1994). The fundamental ob-jectives of competitive intelligence are to avoidsurprises and gain competitive advantage (West,2001). Knowledge has value, but intelligence haspower (Rothberg and Erickson, 2005). We followFuld and define intelligence as a time-sensitiveassessment that will direct someone to act (Fuld,2010). Gilad (Gilad, 1988) offers another usefuldefinition: processed information of interest tomanagement about the present and future envi-ronment in which [a competing entity] is operat-ing.

For Fuld, change will occur and the futurewill not be the same as today. To prepare our-selves for that future, we look to signs of earlywarning (the ability to see into the future) in theform of leading indicators. Early warning con-sists of four very simple and ”intelligent” steps,which we adapt for our purpose: (1) drawingthe road map of possible futures, (2) identifyingthe signals we need to watch for each of thesefutures, (3) constructing automated scripts towatch those signals in the course of a machine-played game analysis and exploration, and (4)

making sure we create an approach to act quicklyonce one of the futures we have identified (aspromising) begins to emerge (Fuld, 2010). Weagree with Fuld that the signals are out there -we just need to construct a diagnostic indicatorsensitive enough (but not prone to false alarms)to guide our exploration efforts. We ask not,”Is this perfectly accurate?” But rather, ”Is thissufficient to make a good decision?” (Hooper andScott, 1996).

We use competitive intelligence to reducethe risk that our exploration efforts will not bepromising. We identify intelligence - not infor-mation - as helpful to us and our programmedmachine in choosing these paths (Fuld, 1995).By actively seeking intelligence and learning howto use it, we hope to turn information into apowerful weapon that will give us a competi-tive advantage (Fuld, 1995) - information bothvalid and timely becomes war’s most powerfulweapon (Luttwak, 2001). Each competitor play-ing a game has virtually the same access to infor-mation. We envision, with Fuld, that the playerthat is more effective in converting available in-formation into actionable intelligence will endup winning the game. Without intelligence, youmay succeed in winning a battle or two, but youcan’t expect to win the war (Fuld, 1995).

Gilad (Gilad, 1988) explains how competi-tive intelligence translates into competitive ad-vantage, which we modify slightly for the pur-poses of a machine playing a game. The purposeof the data collected is to enable the machinegame-player to arrive at an assessment of thecurrent situation on the board (in terms of itsposition) based on the key success factors. Thebirth of a strategy follows logically and chrono-logically the assessment of the situation. This, inturn, is based on the environmental intelligence

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picture provided by the competitive intelligenceprogram. For Gilad, and for us, the better thatinput, the better the resulting strategy.

For a business example, one of us (JLJ) re-cently filled out a multi-question employee satis-faction survey from his current employer - STGInc. This was necessary, we were told, ”to con-tinue to improve processes to help achieve ournumber 1 Critical Success Factor - to be recog-nized as one of the best places to work.” Thesurvey was actually conducted by another com-pany hired for that purpose, in order to allowemployees the ability to respond anonymously.We were told that ”Once the survey closes, thedata is analyzed, charts and graphs are createdand recommendations are made by HR Innova-tive Solutions.” When the period of time allowedfor employees to complete the survey passed, wewere then told the results - ”The overall sat-isfaction rating (OSR) was X.XX out of 4.06;”(we were asked to keep the results proprietary,but they were very good) ”an overall SatisfactionRating of 3.71 is considered industry standard.”One question we were asked was ”What wouldmake our company a better place to work?”

We see this example as competitive intelli-gence in action, supporting the analysis of suc-cessful achievement of critical success factors,which drive corrective actions. We can identifywith Greene’s position (Greene, 1966) that man-agement doesn’t care about intelligence sources,nominal costs of collection, or clever filing tech-niques; they want (reliable) answers to questions,and they want the answers promptly. Intelli-gence is, in every sense, a control system - theintelligence system keeps the competing entityon track with the external environment - withreality (Page, 1996). STG could have used an in-expensive method for the survey, such as e-mail

or instructing managers to pass out forms andcollect them. Employees might then be less thanhonest in their response, fearing that it couldsomehow be tracked back to them. STG man-agement determined that an accurate (althoughlikely expensive) survey was necessary to makeprecise changes to company policies in pursuit ofachieving good results in chosen critical successfactors.

We proceed now with Kahaner’s first partof the intelligence cycle - planning and direction(Kahaner, 1997) - which involves a clear under-standing of the user’s needs (key success factors),and establishing a collection and analysis plan.What is essential here is knowing what needsto be known, at the moment it is needed foruse (Rothberg and Erickson, 2005), and turn-ing that knowledge into appropriate diagnosticaction. Rockart (Rockart, 1979) defined Criti-cal Success Factors as the limited number of ar-eas in which satisfactory results will ensure suc-cessful competitive performance for the individ-ual, department, or organization. Continuing,he felt that they are the few key areas wherethings must go right for the competitor to flour-ish. If results in these areas are not adequate,the organization’s efforts for the period will beless than desired. We agree with Rockart thatthe critical success factors are areas of activitythat should receive constant and careful atten-tion from management. Specifically, the currentstatus of performance in each area should be con-tinually measured.

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14 From Orientors to Indica-tors to Goals

The universal response to novelty in animalspecies is the ”orienting response” - an appraisalinitiating a chain of cognition aimed at findingthe most finely tuned response (Goleman, 2005).One orients as an initial step in a strategy forcreating coherent action, which Rumelt (Rumelt,2011) sees as being preceded by diagnosis and theselection of a guiding policy. Once we have de-cided which issue is preeminent we are preparedto direct and constrain action. A guiding pol-icy creates advantage by anticipating the actionsand reactions of others, by reducing the complex-ity and ambiguity in the situation, by exploitingthe leverage inherent in concentrating effort on apivotal or decisive aspect of the situation, and bycreating policies and actions that are coherent,each building on the other rather than cancelingone another out (Rumelt, 2011).

We have found six basic sys-tem orientors (existence and sub-sistence, effectiveness, freedom ofaction, security, adaptability, co-existence) that apply to all au-tonomous self-organizing systems -Hartmut Bossel

We identify and adapt the framework in-dependently arrived at by Vickers, Bossel andMax-Neef (Vickers, 1959) (Bossel, 1976) (Bossel,1977) (Bossel, 1994) (Bossel, 1998) (Bossel,1999) (Bossel, 2007) (Muller and Leupelt, 1998)and (Max-Neef, 1991) to conceptualize the crit-ical success factors which guide diagnostic ac-tion, which in our vision share much with thatof an ecosystem. We seek indicators which re-alize Bossel’s six basic high-level orienting prop-erties of existence and subsistence, effectiveness,

freedom of action, security, adaptability, and co-existence.

We theorize with Bossel that these proper-ties are each vital diagnostic indicators of suc-cessful system development, and we aim to orientour initial diagnostic exploration efforts alongpaths which seek to improve the weakest of theseproperties. Holistic indicators allow us to under-stand if the system under study is globally fol-lowing a path that takes the system to a ”better”or to a ”worse” state (Jorgensen and Fath, 2007).These indicators must give a fairly reliable andcomplete picture of what really matters (Bossel,1998).

If a system is to be viable in the long run, aminimum satisfaction of each of these basic ori-entors must be assured (Bossel, 1994). We the-orize with Bossel that the behavioral responseof the system is conditional on the chosen in-dicator set: problems not perceived cannot beattacked and solved (Bossel, 1977). Meaning-ful non-routine behavior can only occur by ref-erence to orientors, which are therefore key el-ements of non-routine behavior (Bossel, 1977)(Bossel, 2007). The possible successes of unori-ented non-routine behavior can be only chancesuccesses (Bossel, 1977) (Bossel, 2007). Bosseleven goes so far to declare (Bossel, 2007) thatorientor-guided decision-making will lead to sus-tainable development without requiring specifi-cation of intermediate or end states. A sustain-ability indicator should point the way to a courseof action (Bell and Morse, 2008). What is lack-ing is not data but an understanding of whatis important and the resolve to act (Lawrence,1997).

We directly follow Lockie (Lockie et al.,2005) in our conceptual foundation of indicators,in which we directly quote due to the importance

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of the concept. Indicators are instruments to de-fine and monitor those aspects of a system thatprovide the most reliable clues as to its overallwell-being. They are used, in other words, toprovide cost and time-effective feedback on thehealth of a system without necessarily examiningall components of that system. According to pro-ponents, the validity of indicators is based on thedegree to which the wider network of componentsand relationships in which they are situated linktogether in a relatively stable and self-regulatingmanner, and the degree to which the indicatorsthemselves represent the most salient or criticalaspects of the system that can be monitored overtime.

We also follow Lawrence (Lawrence, 1997)and declare that indicators are intended to an-swer the question: ”How might I know objec-tively whether things are getting better or get-ting worse?”. What we are really interested inare directional indicators, which are less focusedupon numerical representations and are more fo-cused upon action, as in ”I should do somethingabout this.” For data to be useful to us, it mustdescribe things which actually matter to our fu-ture. Objective and relevant data needs to beconverted into information if it is to be usefulin the development of sustainability indicators(Lawrence, 1997). Information that is measuredshould evoke happiness when the situation im-proves and unhappiness when it gets worse. Ifthe change doesn’t matter, we are not monitor-ing the right data (Lawrence, 1997).

Needs provoke real impulses foraction... when sufficiently gratifiedcease to exist as active determinantsor organizers of behavior

Maslow (Maslow, 1987) notes that needs,

along with their partial goals, when sufficientlygratified cease to exist as active determinants ororganizers of behavior. Bisogno (Bisogno, 1981)notes that the term need means a state of dis-satisfaction provoked by the lack of somethingfelt as being necessary. Needs provoke real im-pulses for action, which for Max-Neef, become(instead of a goal) the motor of development it-self (Max-Neef, 1991). Importantly for Bisogno,needs which would appear to be essential in aparticular moment, are no longer so when thesecircumstances - time, place, (or for Maslow astate of satisfaction), change. A need becomesa necessity when its satisfaction is absolutely in-dispensable to a given state of affairs (Bisogno,1981).

Needs, however, are theoretical constructs(Tobar-Arbulu, 1987). The ”truth” of a needcannot, therefore, be proven in a direct physicalway. The existence of a need can be concludedindirectly either from postulation or from the re-spective satisfiers that a person (or entity) usesor strives for, or from symptoms of frustrationcaused by any kind of nonsatisfaction (Tobar-Arbulu, 1987). We speculate with Tobar-Arbuluthat a list of needs could serve as a guidelinefor monitoring conditions adequate for develop-ment, survival, or even moment-by-moment op-erations. Satisfaction of needs could inspire usto awareness, in addition to serving as a goal ofdevelopment (Tobar-Arbulu, 1987).

In the absence of a ”desire” that picks outone possibility rather than another (Olafson,1995), our whole active relation to the future,as well to possibilities as such, would becomedeeply problematic. The conclusion to which allthis points (Olafson, 1995) is that if anything canbe said to orient us toward the future - any fu-ture - and thus to possibility as such, it is surely

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desire. This is also to say that it is desire thatdiscloses such possibilities to us in a ”primor-dial” way. Olafson develops the concept of per-ception as the detection of presence. A desirebecomes ”present” to us by the unique charac-teristic of an absence (Olafson, 1995), in whichcase we ”need” to do something in the future tomake the absence go away.

This all becomes elevated in importancewhen we consider the possibility that guidelinesfor making decisions follow from basic systemneeds (Bossel, 1981). The ”normal” functioningof a given system requires the satisfaction of cer-tain basic needs characteristic of the system andof its function. When deprived of satisfaction ofany one of the basic needs, the system will ceaseto function in the ”normal” mode and possiblycease to function altogether. Basic needs are ir-reducible and one basic need cannot substitutefor another (Bossel, 1981).

Health and fitness of a system re-quire adequate satisfaction of each ofthe system’s basic orientors. Plan-ning, decisions, and actions in soci-etal systems must therefore always re-flect at least the handful of basic ori-entors (or derived criteria) simulta-neously. Comprehensive assessmentsof system behavior and developmentmust also be multi-criteria assess-ments...

We see a value in the two-phased approach of(Bossel, 1976) and (Bossel, 1994): first, a certainminimum qualification must be obtained sepa-rately for each of the basic orientors. A deficitin even one of the orientors potentially threatensour long-term survival from our current position.Our computer software will have to focus its at-tention on this deficit. Only if the required min-

imum satisfaction of all basic orientors is guar-anteed is it permissible to try to raise systemsatisfaction by improving satisfaction of individ-ual orientors further - if conditions, in particularour opponent, will allow this.

We see goal functions as operating to trans-late the fundamental system needs expressed inthe basic orientors into specific objectives linkingsystem response to properties observed on thechess board. We conceptualize that goal func-tions emerge as general properties in the coevo-lution of the chess position and dynamic, futuredevelopment. They can be viewed as specific re-sponses to the need to satisfy the basic orientors.For example, mobility is related to adaptability,constraints relate to coexistence, king safety isrelated to the orientors of security and existence,virtual existence and stress are related to effec-tiveness, material is related to existence, securityand adaptability, etc. We can creatively comeup with new indicators to orient our diagnosticexploration, but we see them fitting within theproposed framework and ’dimension of concern’as outlined previously.

We see the vital orientors, which express ourvalues, as operating together to create a selectionmethod for our immediate goals. The goals weseek are not specific objects, but rather changesin our relations or in our opportunities for relat-ing (Vickers, 1995).

...a system’s development will beconstrained by the orientor that iscurrently ’in the minimum’. Partic-ular attention will therefore have tofocus on those orientors that are cur-rently deficient. -Hartmut Bossel

We see an interesting similarity with the”ABC” (airway, breathing, circulation) priority

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system used in emergency room and rescue op-erations when deciding what to do next withan accident victim. The rescue team performsthe set of vital diagnostic tests and then focusestheir immediate attention on the critical indica-tor that scores the lowest. The ”health” of thevictim (and in fact the direction to take next)would not be based on an average or summa-tion score of the vital indicators, but instead onthe vital indicator which scores the lowest. Thegoal, then would be to do something which im-proves the score returned by that indicator. Ifmore than one indicator is below a certain criti-cal threshold (such as, the patient is not breath-ing and there is no circulation), then Cardiopul-monary Resuscitation (CPR) would need to beperformed - improvement of the airway, breath-ing and circulation indicators are all simultane-ously attempted.

Our experience in computer chessover the past few years seems to in-dicate that future chess programs willprobably benefit from evaluation func-tions that alter as the general chessenvironment changes. -Peter Frey,Chess Skill in Man and Machine,1977

We also see a similarity to the commonyearly performance evaluation which is tradi-tionally performed by American management oneach company employee, or even a report cardgiven to a student. The ritual evaluation will liststrengths, weaknesses, and expectations, and itis also common to list improvements necessaryto reach the next performance level. The smartworker will examine his vital, multi-criteria di-agnostic assessment and orient his or her efforts(during the next year) towards improving theweakest scoring of these indicators, while con-

tinuing to leverage strengths and meet the listedexpectations.

We see similarities to Festinger’s principleof cognitive dissonance (Festinger, 1957), wherea perception of dissonance between an observedindicator and a desired value leads to activityoriented towards reduction of the perceived dis-sonance. Festinger believes that reduction of dis-sonance is a basic process in humans, precededfirst by perception and identification.

the set of basic orientors derivesfrom the question: ”Given the globalfeatures of the system and of its envi-ronment, what basic orienting dimen-sions must the system refer to in itsnonroutine behavior, and in partic-ular in fundamental behavioral deci-sions in order to fulfill the global in-struction of the supreme orientor?” -Hartmut Bossel

We see the chess programs of the future asaddressing this conceptual foundation, in cre-ative ways and approaches that cannot yet beenvisioned by today’s developers. Our concep-tualization of stress management and the con-struction of resilient positions as indicators are,ideally, part of an operational realization of thesix orientors. If our concept fails as an orientor ofdiagnostic exploration efforts, then it needs to bemodified or itself re-engineered. Perfectly usableindicators might overlap, or require too muchprocessor time to implement. Perhaps what is re-quired is the art of a talented programmer/chessplayer to select a set of indicators which also ori-ent with effective insight.

What we are saying is simply that we mustpay attention to each of these orientating qual-ities separately - we should not just roll them

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up into a grand, universal ”number” and expectto effectively and efficiently drive our diagnos-tic exploration efforts in that fashion. A weak-ness in one of the six orientors critically impactssustainable development in the uncertain futureand cannot be ”made up for” with a higher scorefrom the others. A simple mechanism for scoringour diagnostic exploration efforts, such as aver-aging the lower two indicators (of six total, onefor each orientor), or using the lowest if it is farbeneath the others, will make sure that the ma-chine pays attention to (and focuses attentionon) those orienting parameters that are in needof improvement.

Our present [evaluation function]is blind to the simplest phenomena.The evaluator gladly accepts a posi-tion in which the computer is a knightahead although its king is out in thecenter of the board surrounded by hos-tile enemy queens and rooks. -DavidSlate and Lawrence Atkin, Chess Skillin Man and Machine, 1977

We seek sustainability itself as a goal, whichmakes sense because our opponent can offer usanything else we would otherwise seek (and ini-tially appearing to move us closer to checkmate),but in a way that (for us) might not be sustain-able in the long run, due to the hidden effects ofdynamic complexity. We can measure sustain-ability, in its simplest form, by the weakest ofour vital diagnostic indicators. A weighted sumof vital indicators would be used for endpointevaluation purposes, possibly including a limiteron each parameter.

These orienting indicators, which help us toconstruct a picture of the state of our environ-ment on which we can base intelligent decisions

(Bossel, 1998), can all be based on a commonfoundation, such as cumulative stress, but witha weighting that aims to highlight the partic-ular dimension of concern. Our goal is simplyto determine, through appreciative indicators,”What matters most now?” (Vickers, 1995) andthen to (initially) focus attention on any movewhich we perceive to make progress in that areaor dimension of concern. We choose to behavelike an efficient business manager, besieged bynumerous concerns and pressed for time, decid-ing how to allocate attention in the face of con-stant demands, both known and unknown, in dy-namically creating a response to the importantand expensive (if wrong) question ”what do I donow?”. Curiously, how we allocate the attentionof the machine becomes a decision of profoundimpact on the quality of the move we will laterdecide to make.

test the [strategic] principle for itsability to promote and guide action.In particular, assess whether it ex-hibits the three attributes of an effec-tive strategic principle...

What good is being a piece up if your Kingis in the center of the board, surrounded by hos-tile enemy pieces? Better to see if we can returnthe King to a safe place, even at the price of ma-terial, so that we can continue the sustainabledevelopment of our position in the future. Wetherefore orient our attention and future search-ing in ways to improve King safety.

Our immediate goals, therefore, emerge fromthe weakest indicators (results) of the vital diag-nostic tests, and operate to orient our diagnosticexploration efforts along lines that allow sustain-able development in the uncertain future.

The orientors represent our wants or inten-

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tions - an intention doesn’t exactly require anydeep calculation or plan. We can explore themoves that (partially) satisfy our wants, andby simple focused learning, examine the conse-quences of what emerges as we slide forward afew promising moves into the future. We needboth the readings and the norms. For only if weknow both where we are and where we want to gocan we act purposefully in seeing about gettingthere (Laszlo, 1996). A need is seen as a process,with no beginning and no end, of satisfaction anddissatisfaction, undulating through time withsometimes slow, sometimes quick rhythms, withno resting point (Galtung, 1980). Life is seen asan effort to extinguish lamps in the console sig-naling ”need unsatisfied/unattended” (Galtung,1980).

...Will it force tradeoffs? Will itserve as a test for the wisdom of a par-ticular business move, especially onethat might promote short-term profitsat the expense of long-term strategy?...Does it set boundaries within whichpeople will nonetheless be free to ex-periment? -Gadiesh, Gilbert, Trans-forming Corner-Office Strategy intoFrontline Action

We tentatively envision the following chess-based dynamic leading indicators as orientorsand strategic guides to action, based on Bossel’scollection: existence and subsistence (short-range probing and quick exploration of promisingmoves indicates that position is sustainable andgood moves are available), effectiveness (mate-rial, adjusted by positional engagement of eachpiece - level of stress created by pieces makessufficient short- and long-range threats to re-duce resilience of opponent while sufficientlyavoiding opponent’s threats), freedom of ac-

tion (mobility - including 2nd and 3rd order,penalty if pieces are trapped or pinned, mul-tiple good moves available), security (dynamicKing safety), adaptability (positional score is notdecreasing with increased diagnostic explorationdepth), coexistence (effective use of constraintsto weaken effect of enemy pieces, while avoidingenemy constraints, pieces are not constrained byfriendly pieces). We simply ask, ”What areas ofcompetitor activity do we feel need close atten-tion?” (Fuld, 1995). With regard to the indi-cated direction for exploration, we ask not, ”Isthis perfectly accurate?” But rather, ”Is this suf-ficient to make a good initial decision?”

when one is modeling some situ-ation... it is reasonable to use anyassumptions that work, but it is notreasonable to make these assumptionsinto ”laws,” or to forget that these areassumptions that people made in thefirst place. -William Byers

Hubert points out (Hubert, 2007) that whatis generally missing in sustainability programsis a set of leading indicators (such as thoseproposed above) that provide signals of systemchanges that will ultimately affect the system’soutput, and are timely enough to allow inter-vention that can change the outcomes. Whenproperly done, these leading indicators provideinsight into the state of a system’s health. ForHubert, an unbalanced dependence on laggingindicators (such as rewarding pieces for sittingon good squares) is to be fooled by early suc-cesses, or what is sometimes called the ”gettingbetter before it gets worse” - focusing on an out-come (maximum yield) rather than on leadingindicators of health.

Without leading indicators, we cannot easily

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distinguish early successes from the early stagesof looming failure. Additionally, Hubert feelsthat the common cause behind many resourcemanagement failures is this focus on managingfor a single outcome, which first improves per-formance, but later leads to system collapse. Fi-nally, Hubert declares his opinion that we cansustain systems that are evolving when we un-derstand that all we need to do is think in termsof sustaining a system’s health and functionalityrather than its specific form or condition (Hu-bert, 2007).

A frame provides an official main focus forattention, in accord with the business at hand(Goleman, 2005). The frame is highly selective;it directs attention away from all the simultane-ous activities that are out of frame. What is outof frame can easily go unperceived - any frame atall, in fact, defines a narrow focus where the rel-evant schemas direct attention, and a broad, ig-nored area of irrelevance (Goleman, 2005). Thedominant track, however, has to be picked outof the entire assemblage of activity (Goleman,2005).

Our orientors create parallel tracks - inframe and out of frame - creating a structurein social awareness that duplicates the divisionwithin the mind between conscious and uncon-scious (Goleman, 2005). What is out of frameis also out of consensual awareness - indeed, thesocial world is filled with frames that guide ourawareness toward one aspect of experience andaway from others. But we are so accustomedto their channeling our awareness that we rarelynotice that they do so (Goleman, 2005).

15 Shannon’s Evaluation Func-tion

Shannon proposed (Shannon, 1950) a simpleevaluation to be performed in relatively quies-cent positions. We wonder out loud if Hegel’sobservation is more correct - that the health ofa ”state” shows itself not in the quietness ofpeace but in the commotion of war (Friedrich,1954). In war, the strength of the cohesion of theparts with the whole is demonstrated (Friedrich,1954). Quiescent evaluations do not (and can-not) measure how far a position will bend beforeit breaks. We suggest that a more accurate eval-uation might roughly simulate the interactions ofwar via diagnostics such as probing to determinemultiple-move constrained mobility of the pieces,and the identification of the lowest-scoring of thesustainability indicators.

Networks are comprised of a set ofobjects with direct transaction (cou-plings) between these objects... thesetransactions viewed in total link di-rect and indirect parts together in aninterconnected web, giving rise to thenetwork structure...

While recent tournaments have shownthat Shannon-style evaluations (combined withalpha-beta pruning and the null-move heuristic)can be used to produce world-class chess pro-grams, we seek an alternate approach with thecapability of even better performance. Programsthat use Shannon’s evaluation often have troublefiguring out what to do when there is no directsequence of moves leading to the placement ofpieces on better squares (such as the center), orthe acquisition of a ”material” gain.

We see a general correlation between the

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placement of a piece on a ”good square” and theability of that piece to inflict stress on the oppo-nent, and to mitigate the effects of stress causedby well-placed opponent’s pieces. We even seethat the concept of mobility has value in a gen-eral sense. However, we see problems with thistechnique being used to build positional pres-sure, such as the kind needed to play an effec-tive game of correspondence chess. The long anddeep analysis produced by the machine is oftenfocused in the wrong areas, as determined by theactual course of the game. We do not attempthere to declare that we are experts in the rea-sons that it ”works”. It is a diagnostic test ofadaptive capacity - a stress test of sorts - whichis remarkably effective in performing a social ac-tion - choosing a move in a game.

...The connectivity of nature hasimportant impacts on both the objectswithin the network and our attemptsto understand it. If we ignore the weband look at individual unconnected or-ganisms... we miss the system-leveleffects. -Jorgensen, Fath, et al., ANew Ecology

The adaptive stress produced by the Shan-non method is not of the type that reduces thecoping capacity of the opponent, or increases ourown resilience, in certain game situations wherepositional play is required. For example, in po-sitions that are empty of tactical opportunities,the machine can be effectively challenged by op-ponents who know how to play a good positionalgame of chess (Nickel, 2005). The terms of theShannon evaluation function do not seem suit-able metrics for guiding diagnostic explorationand planning efforts, in these cases.

Fontana (Fontana, 1989) advises us to ask:what are the stressors, what needs to be done

about them, and what is stopping us from doingit? There is little to be gained from generalizing,if our goal is to identify the stressors, accuratelyassess the levels of stress present, and mobilizeaccording to the results.

16 The Positional EvaluationMethodology

So we need something like a map ofthe future. A map does not tell uswhere we will be going, or where weshould be going - it merely informsus about the possibilities we have...We therefore need a description of thepossibilities ahead of us...

We propose that an approach which at-tempts to increase the oriented positional pres-sure or cumulative stress on the opponent, evenif unresolved at the terminal positions in our di-agnostic exploration efforts, is a viable strategyand has the potential to play a world-class gameof chess. Our strategic intent is to form tar-geted positional pressure (aimed at weakpointsdefined by chess theory and at constraining themovement of the enemy pieces) that will resolveat some future point in time into better posi-tions, as events unfold and gameplay proceeds.At minimum, this pressure will allow for sustain-able evolutionary development as one componentof a resilient position. We will not judge piecesprimarily by the ”squares” they occupy, but in-stead, by our heuristic estimates of the level offlexibly persistent and oriented stress they cancontribute (or mitigate) in the game positionswhich lie beyond our planning horizon.

We construct an orientation/evaluationmethodology with the goal of making our ma-

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chine more knowledgeable with regard to the po-sitional concepts discussed earlier. In designingour methodology, we heed the advice of (Dom-broski, 2000) that this methodology is our test ofeffects and consequences and is our guiding lightin our search for the consequences of our choices.

...Such a map would not have togive us very detailed information...But it should give us a useful imageof what may be ahead, and allow usto compare the relative merits of dif-ferent routes... before we embark onour journey. -Hartmut Bossel

Our orientation/evaluation centers on aheuristic appraisal of the stress we inflict on theopponent’s position, and our mitigation of thestress created by the opponent. We aim to re-duce our opponent’s coping ability through care-ful targeting of stress. The dynamic forces ofchange, acting over time and in a future we of-ten cannot initially see, transform the reducedcoping ability of our opponent, our carefully tar-geted stress, and our resilient position full ofadaptive capacity, to future positions of advan-tage for us.

Perhaps this concept is what inspired BobbyAllison to race most of the 1982 Daytona 500without a back bumper - it fell off after contact-ing another car early in the event (NASCAR,2009). Some drivers accused Allison’s crew chiefof rigging the bumper to intentionally fall off onimpact. Allison’s car without the bumper hadimproved aerodynamics, and the forces of dy-namic change operating over the 500 mile racesupplied the driver with an advantage he usedto win. This odd example is used to suggestthat ”evaluations” of winning chances shouldtake into account the dynamic effects of inter-

acting forces over time, rather than just staticobservations. Other examples (the winged keelof the Australia II yacht and the new loop-keel design, hinged ice skates and performanceenhancing swimsuits come to mind) show howsmall changes, combined with other critical abil-ities and interacting with a dynamic environmentover time, can create a performance advantage.

Sustainability... means, as saidbefore, that only the riverbed, notthe exact location of the river in it,can and should be specified -HartmutBossel

We seek, in similar fashion, to favor certaininteracting arrangements of pieces, such that thedynamic forces of change (operating during theplaying of a game) cause favorable positions toemerge over time, from beyond our initial plan-ning horizon. We seek to re-conceptualize the”horizon effect” to our advantage. We cannotarrange for a bumper to fall off during a chessgame, but we can do the equivalent - we canactively manage the dynamics of change to im-prove the chances for persistence or transforma-tion (Chapin et al., 2009). This would includethe general approaches of reducing vulnerabil-ity, enhancing adaptive capacity, increasing re-silience, and enhancing transformability (Chapinet al., 2009). We manage the exposure to stress,in addition to the sensitivity to stress (Chapin etal., 2009).

We adopt the vision of (Katsenelinboigen,1992), that we define a ”potential” which mea-sures a structure aimed at forcing events in ourfavor. Ideally, one which also absorbs or reducesthe effects of unexpected events.

We follow the suggestion in (Pearl, 1984)to use as a strategy an orientation/evaluation

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based on a relaxed constraint model, one thatideally provides (like human intuition), a streamof tentative, informative advice for managing thesteps that make up a problem-solving process,and use the insight from (Fritz, 1989) and (Ster-man, 2000) that structure influences behavior.

in order to understand what powerrelations are about, perhaps we shouldinvestigate the forms of resistance andattempts made to dissociate these re-lations... The exercise of power... isa way in which certain actions modifyothers... Power exists only when it isput into action, even if, of course, itis integrated into a disparate field ofpossibilities -Foucault

In order to more accurately estimate the dis-tant positional pressure produced by the chesspieces, as well as to predict the future capabilityof the pieces in a basic form of planning (Lakein,1974) (Shoemaker, 2007) we create the softwareequivalent of a diagnostic probe which performsa heuristic estimate of the ability of each pieceto cause and mitigate stress. The objectiveswe select for this stress will be attacking enemypieces, constraining enemy pieces, and support-ing friendly pieces (especially those pieces thatare weak). To support this strategy, we calculateand maintain this database of potential mobilityfor each chess piece 3 moves into the future, foreach position we evaluate.

We update this piece mobility database dy-namically as we evaluate each new leaf posi-tion in our diagnostic exploration efforts. Thisdatabase helps us determine the pieces that canbe attacked or supported in the future (such as2 moves away from defending a piece or 3 movesaway from attacking a square next to the enemy

king), as well as constrained from accomplishingthis same activity. Note that the piece mobil-ity we calculate is the means through which wedetermine the pressure the piece can exert on adistant objective. We can therefore see how mo-bility (as a general concept) can become a vitalholistic indicator of system health and one pre-dictor of sustainable development.

We reduce our bonus for each move that ittakes the piece to accomplish the desired objec-tive. We then consider restrictions which arelikely to constrain the piece as it attempts tomake moves on the board.

For example, let’s consider the pieces in thestarting position (Figure 4).

Figure 4: White and Black constraint map, pieces at thestarting position Legend: Red: pawn constraints, Yellow: Mi-nor piece constraints, Green: rook constraints, Blue-green:Queen constraints, Blue: King constraints

What squares can our knight on g1 influencein 3 moves, and which squares from this set arelikely off-limits due to potential constraints fromthe enemy pieces?

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Figure 5: Influence Diagram and Simulation Diagram, Ng1at starting position Legend: Red - 1 move influence, Yellow- 2 move influence, Green - 3 move influence, Dark Red - 1move influence possibly constrained by opponent piece, DarkYellow - 2 move influence possibly constrained by opponentpiece, Dark Green - 3 move influence possibly constrained byopponent piece, Blue - no influence possible within 3 moves, X -presence of potential constraint ”Power... is diagrammatic... itpasses not so much through forms as through particular pointswhich on each occasion mark the application of a force, theaction or reaction of a force in relation to others” -Deleuze

forces are in a perpetual state ofevolution; there is an emergence offorces... the diagram... exposes a setof relations between forces... it is theplace only of mutation. -Deleuze

We now construct the influence diagram(Shoemaker, 2007) and the simulation diagram(Bossel, 1994) (Figure 5), which are interpretedin the following way. If a piece is on our influ-ence diagram for the knight, then it is possibleto attack it or defend it in 3 moves (this includeswaiting moves or moves which move a piece outof the way). We label this kind of map an influ-ence diagram because it shows the squares thatthe piece can influence in 3 moves, provided thatit is unconstrained in movement by the enemy.

The influence diagram capturesthe behaviorally relevant structure ofthe system. It is therefore the basisfor any simulation model. Becauseof its importance for the success of

model development, the influence di-agram has to be developed with careand precision...

Keep in mind that we need to take into ac-count the location of the other pieces on thechessboard when we generate these diagramsfor each piece. If we trace mobility through afriendly piece, we must consider whether or notwe can move this piece out of the way before wecan continue to trace mobility in that particu-lar direction. If we trace mobility through anenemy piece, we must first be able to spend 1move capturing that piece.

Understanding how power works is the firstprerequisite for action, because action is the ex-ercise of power (Flyvbjerg, 1998). A strongunderstanding of situations where conflict ex-ists must therefore be based on thought thatplaces conflict and power at its center (Flyvb-jerg, 1998). Foucault (Foucault, 1982) defines arelationship of power as a mode of action thatdoes not act directly and immediately on oth-ers. Instead, it acts upon their actions: an ac-tion upon an action, on possible or actual futureor present actions. A relationship of violence, incomparison, acts upon a body or upon things; itforces, it destroys, or it closes off possibilities.We can threaten the knight itself, or the po-tential actions of the knight. The knight makesthreats of its own on the board - its power is ex-ercised rather than possessed (Foucault, 1995).An exercise of power shows up as an affect,since force defines itself by its very power to af-fect other forces (and in turn to be affected bythem)(Deleuze and Hand, 2006). Foucault’s the-ory of power is about using tools of analysis tounderstand power, its relations with rationalityand knowledge, and aims to use the resulting in-sights precisely to bring about change (Flyvbjerg

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and Richardson, 2002).

...To capture their dynamics cor-rectly, real systems cannot usually berepresented by linear approximations-Hartmut Bossel

We focus on power relations because powerproduces knowledge (Foucault, 1995). Power andknowledge directly imply one another - there isno power relation without the correlative consti-tution of a field of knowledge, nor any knowledgethat does not presuppose and constitute at thesame time power relations (Foucault, 1995). ForBertrand Russell (Russell, 2004), the laws of so-cial dynamics are only capable of being statedin terms of power in its various forms. Powermust be met by power. The only way to containaggression and cope with hostility is to build upand intelligently manipulate consequential con-straints, threats and force (Jervis, 1976).

[Foucault] insists that the princi-pal characteristic of power is alwaysto manifest itself in a discourse aboutsomething other; power can only beeffective - and tolerated - when somepart of it is hidden... it can only be...analyzed in the places it both inhab-its and vacates simultaneously, andhence viewed only indirectly. -HaydenWhite

We strategically apply Foucault’s conceptionof power relations to the pieces on the gameboard- we see the maneuvers in terms of the networkof relations, constantly in tension, and as a per-petual battle rather than a simplistic conquest ofterritory (Foucault, 1995). The knowledge we ac-quire is meaningless if it is not derived from thesemaneuvers and the corresponding power rela-tions. For Foucault (and in our interpretation,

the situation involving the pieces on the game-board), power is a machine in which everyone iscaught, those who exercise power just as muchas those over whom it is exercised - it becomesa machinery that no one owns (Foucault, 1980).We suggest that an understanding of planningthat is practical, committed and ready for con-flict provides a superior paradigm to planningtheory - planning is inescapably about conflict:exploring conflicts in planning, and learning towork effectively with conflict can be the basisfor a strong planning paradigm (Flyvbjerg andRichardson, 2002).

Returning to Figure 5, we can determinethat the white knight on g1 can potentially at-tack 3 enemy pieces in 3 moves (black pawns ond7, f7 and h7). We can defend 8 of our ownpieces in 3 moves (the knight cannot defend it-self). One way to interpret Figure 5 is as anorganized puzzle-solving gestalt which is itself a’picture’ of something, A, which is then to beapplied, non-obviously, to provide a new ’way ofseeing’ something else, B. This is what (Master-man, 1970) calls a Kuhnian paradigm.

We decide to reward pieces for their poten-tial ability to accomplish certain types of worth-while positional objectives: attacking or con-straining enemy pieces, defending friendly pieces,attacking squares near our opponents king (es-pecially involving collaboration), minimizing ouropponent’s ability to attack squares near our ownking, attacking pieces that are not defended orpawns that cannot be defended by neighboringpawns, restricting the mobility of enemy pieces(specifically, their ability to accomplish objec-tives), etc. In this way, we are getting real aboutwhat the piece can do. The bonus we give thepiece is 1. a more precise estimate of the piece’sability to become strategically engaged with re-

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spect to causing or mitigating stress and 2. op-erationally based on real things present on thechessboard. In this way, our positional orienta-tion/evaluation methodology will obtain insightnot usually obtained by a computer chess pro-gram, and allow our machine to take positive,constructive action (Browne, 2002). It is still anestimate, but the goal here is to orient our di-agnostic exploration efforts on likely moves in apositional style of play, and to evaluate positionsfrom a more positional point of view.

What does the orientation/evaluationmethodology look like for the proposed heuris-tic? We model (and therefore estimate) thepositional pressure of our pieces, by following atwo-step process:

1. We determine the unrestricted future mo-bility of each chess piece 3 moves into the future,then

2. We estimate the operating range or levelof engagement of the pieces by determining thelimiting factors or constraints that bound the un-restricted mobility.

The concept of using limiting factors isbriefly mentioned (Blanchard and Fabrycky,2006) in the context of Systems Engineering.(Lukey and Tepe, 2008) argue that an impor-tant aspect of cognitive appraisal is the extent towhich stress-causing agents are perceived as con-trolled. Balancing processes such as constraints(Anderson and Johnson, 1997) seek to counterthe reinforcing loops created by a piece creatingstress, which, if unconstrained, can potentiallycreate even more stress (perhaps in combina-tion with other pieces). Once we have identifiedthe limiting factors, we can more easily exam-ine them to discover which ones can be alteredto make progress possible - these then becomestrategic factors.

The consideration of constraints is a partof the decision protocol of Orasanu and Con-nolly (Orasanu and Connolly, 1993) and (Pless-ner et al., 2008) which also includes the iden-tification of resources and goals facing the de-cision maker. We therefore reduce the bonusfor accomplishing objectives (such as, attackingan enemy piece or defending a friendly piece) ifthe required moves can only be traced throughsquares that are likely to result in the piece be-ing captured before it can accomplish its objec-tive. We also reduce the engagement bonus formobility traced through squares where the pieceis attacked but not defended. We may use an-other scheme (such as probability) for determin-ing stress-application reduction for piece move-ment through squares attacked both by friendlyand enemy pieces where we cannot easily re-solve whether or not a piece can trace mobilitythrough the square in question (and thereforecreate stress). We think in terms of rewarding aself-organizing capacity to create stress out of thevaried locations of the pieces and the constraintsthey face (Costanza and Jorgensen, 2002).

We reward each piece for its predicted abil-ity to accomplish strategic objectives, exert po-sitional pressure, and restrict the mobility of en-emy pieces, based on the current set of pieces onthe chess board at the time we are calling ourorientation/evaluation methodology. Using an-ticipation as a strategy (van Wezel et al., 2006)can be costly and is limited by time constraints.It can hurt our performance if it is not done withcompetence. An efficient compromise betweenanticipative and reactive strategies would seemto maximize performance.

We give a piece an offensive score based onthe number and type of enemy pieces we can at-tack in 3 moves - more so if unconstrained. We

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give a piece a defensive score based on (1) howmany of our own pieces it can move to defend in 3moves and (2) the ability to mitigate or constrainthe attacking potential of enemy pieces. Again,this bonus is reduced for each move it takes toaccomplish the objective. This information is de-rived from the influence diagram and simulationdiagram we just calculated. Extra points can begiven for weak or undefended pieces that we canthreaten.

The proposed heuristic also determines kingsafety from these future mobility move maps.We penalize our king if our opponent can movepieces into the 9-square template around ourking within a 3 move window. The penalty islarger if the piece can make it there in 1 or 2moves, or if the piece is a queen or rook. We pe-nalize our king if multiple enemy pieces can at-tack the same square near our king. Our king isfree to move to the center of the board - as long asthe enemy cannot mount an attack. The incen-tive to castle our king will not be a fixed value,such as a quarter pawn for castling, but ratherthe reduction obtained in the enemy’s ability tomove pieces near our king (the rook involved inthe castling maneuver will likely see increasedmobility after castling is performed).

The king will come out of hiding naturallywhen the number of pieces on the board is re-duced and the enemy does not have the poten-tial to move these reduced number of pieces nearour king. We are likewise free to advance thepawns protecting our king, again as long as theenemy cannot mount an attack on the monarch.The potential ability of our opponent to mountan attack on our king is the heuristic we use asthe basis for king safety. Optionally, we will con-sider realistic restrictions that our own pieces canmake to our opponent’s ability to move pieces

near our king.Pawns are rewarded based on their chance to

reach the last rank, and what they can do (piecesattacked and defended in 3 moves, whether ornot they are blocked or movable). The piecemobility tables we generate should help us iden-tify pawns that cannot be defended by otherpawns, or other pieces - it is this weakness thatwe should penalize. Doubled or isolated pawnsthat cannot be potentially attacked blockaded orconstrained by our opponent should not be pe-nalized. Pawns can be awarded a bonus basedon the future mobility and offensive/ defensivepotential of a queen that would result if it madeit to the back rank, and of course this bonus isreduced by each move it would take the pawn toget there.

The packets that organize infor-mation and make sense of experienceare ”schemas,” the building blocks ofcognition. Schemas embody the rulesand categories that order raw expe-rience into coherent meaning. Allknowledge and experience is packagedin schemas. Schemas are the ghostin the machine, the intelligence thatguides information as it flows throughthe mind. -Daniel Goleman

The information present in the future mo-bility maps (and the constraints that exist onthe board for the movement of these pieces) al-low us to better estimate the positional pres-sure produced by the chess pieces. From thesecalculations we can make a reasonably accu-rate estimate of the winning potential of a posi-tion, or estimate the presence of positional com-pensation from a piece sacrifice. This orienta-tion/evaluation score also helps orient the diag-nostic exploration process, as the positional score

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is also a measure of how sustainable the positionis and helps us determine the positions we wouldlike to explore first.

In summary, we have created an initialmodel of positional pressure which can be usedin the orientation/evaluation methodology ofa computer chess program, which can be re-fined in diagnostic tournaments of many shortgames. (Michalewicz and Fogel, 2004) remindus that models leave something out, otherwisethey would be as complicated as the real world.Our models ideally provide insight and identifypromising paths through existing complexity.

(Starfield et al., 1994) emphasize that prob-lem solving and thinking revolve around themodel we have created of the process understudy. We can use the proposed model of po-sitional pressure to direct the machine to ori-ent the diagnostic exploration efforts on moveswhich create the most stress in the position as awhole. For our diagnostic exploration efforts, wedesire a proper balance between an anticipatoryand a reactive planning strategy. We desire ourforecast of each piece’s abilities to help us antic-ipate its effectiveness in the game (van Wezel etal., 2006), instead of just reacting to the conse-quences of the moves.

By identifying the elements and processes inour system (Voinov, 2008), identifying the limit-ing factors from the interactions of the elements,and by answering basic questions about space,time and structure, we describe and define theconceptual model of our system.

17 Observations from Cogni-tive Science

We make the following observations about ourapproach, from (Wood, 2009), which in our vi-sion also apply to the concept of a machine play-ing a game.

Our motives and needs, for whatever wechoose to do, affect what we see and don’t see.After carefully selecting what we choose to no-tice, we need somehow to make sense of theseperceptions and form strategic guides for our be-havior. Wood declares that the most useful the-ory for explaining how we organize perceptionsis constructivism, which is the theory that we or-ganize and interpret experience by applying cog-nitive structures called schemata.

We use four types of cognitive schemata tomake sense of perceptions: prototypes, personalconstructs, stereotypes, and scripts. Scripts areguides to action based on experiences and obser-vations. A script consists of a sequence of ac-tivities that identify what we and others are ex-pected to do in certain specific situations. Manyof our daily activities are governed by scripts,although we’re often unaware of them. We the-orize, based on the interpretation of (Honeycuttand Cantrill, 2001) that scripts are a kind of au-topilot, that much subconscious activity whichtakes place in playing a game consists of follow-ing scripts, triggered by perceptions. In most ofthese activities, we use scripts to organize per-ceptions into lines of action. The script tells uswhat to do, in our case - how to gather and or-ganize information, when we find ourselves in ageneral or even a particular situation.

Scripts represent generalized knowledge(Lightfoot et al., 2009) and as such, can be used

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to command a machine to take actions (or figureout what is likely to happen next) in a general-ized situation - such as addressing or determiningthe needs of a position in a board game.

For (de Wit and Mayer, 2010), Knowledgethat people have is stored in their minds in theform of ’cognitive maps’. These cognitive mapsare representations in a person’s mind of howthe world works. A cognitive map of a certainsituation reflects a person’s belief about the im-portance of the issues and about the cause andeffect relationships between them. A person’scognitive map will focus attention on particu-lar phenomena, while blocking out other data asnoise, and quickly make clear how a situationshould be perceived. Cognitive maps help to di-rect behavior, by providing an existing repertoireof ’problem-solving’ responses (also referred to as’scripts’) from which as appropriate action canbe derived.

Our machine will use scripts to, among otherthings, construct a map showing how fully en-gaged a piece is in the game. Maps are guidesto action (Hahlweg and Hooker, 1989) becausethey depict genuine invariant relationships thatexist, in this case, among the pieces on the gameboard. We will also use scripts to manage thestress in a position, along particular dimensionsof concern, and to manage diagnostic explorationefforts.

For Markman (Markman, 2012), it is habitsrather than scripts which explain certain cog-nitive processes. The key signature of a habitis that it is an action you can perform auto-matically without having to think about it con-sciously. For Markman, whenever there is a rou-tine that you do in the same way all the time,you develop a habit for it so that you don’t haveto think about it explicitly any more. We ap-

ply this concept to the simple tasks of gather-ing information about the relationships amongthe pieces when considering what move to playin a game - we might have thought about thisexplicitly when learning to play the game, butafter years of experience we won’t think aboutthe process of doing the behavior any more.

Markman explains that the mind is con-stantly looking to create habits (Markman,2012), and implies that the repetitive tasks ofgathering and analyzing information in playinga game might become automated, so that we arenot even consciously aware of what we are doing.For Markman, smart thinking requires develop-ing smart habits to acquire high-quality knowl-edge and to apply this knowledge to achieve yourgoals (Markman, 2012).

A script codifies the schemas for a particu-lar event; it directs attention selectively, point-ing to what is relevant and ignoring the rest - acrucial factor for programming computers (Gole-man, 2005). A computer program has the ca-pacity to make endless inferences about and re-sponses to a situation - a script allows those in-ferences to be channeled along paths that makesense for a given event (Goleman, 2005).

18 Serious Play Can Lead toSerious Strategy

We follow (Brown, 2009) and (Sutton-Smith,2001) in a conceptualization of play that willform one foundation of our automated diagnosticexploration efforts.

Humans adopt play as a foundational be-havior that guides exploratory activity and insome cases becomes a basis for acquiring knowl-edge. Play is the basis of all art, games, books,

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sports, movies, fashion, fun, and wonder (Brown,2009). Play is the vital essence of life - it is whatmakes life lively (Brown, 2009). However, a ma-chine does not know how to play. It simply doeswhat we tell it to do, so we must tell it how toplay with the pieces on the board and the re-lationships among these pieces. Why must ourmachine play? because, Play is the answer tothe question, How does anything new ever comeabout? (Jean Piaget).

We further conceptualize play (Sutton-Smith, 2001) as the extrusion of internal men-tal fantasy into the web of external constraints.Additionally, we adopt the practical aspect thatplay seems to be driven by the novelties, excite-ments, or anxieties that are most urgent to theperceptions of the players (Sutton-Smith, 2001).Finally, we note that the imagination makesunique models of the world, some of which leadus to anticipate useful changes - the strategicflexibility of the imagination, of play, and of theplayful is the ultimate guarantor of our game-based survival (Sutton-Smith, 2001). Play liesat the core of creativity and innovation (Brown,2009).

We desire our machine to always be busymaking up its own work assignments (Paley,1991). Specifically, the ”work assignments” in-volve choosing our courses of action and adjust-ing those courses based on the internal satisfac-tions we receive (Henricks, 2006). We desire fromour machine a behavior similar to ”playfulness”,and a set of creative, inquisitive, exploratory ori-entations centered on an object-based model ofthe game-world (Henricks, 2006). We desire anactivity of directed exploration, object manipu-lation and precise appraisal. We seek to managethe exploration of the new. This conceptuallyinvolves the creation of small-scale experiments

that can be run outside the mainstream man-agement systems and learned from (Valikangas,2010). Whatever we do, we do not perform asimmutable policy, but as an experiment. We usethe action to learn. Learning means the willing-ness to go slowly, to try things out, and to collectinformation about the effects of actions, includ-ing information that the action is not working(Meadows et al., 2005). We resort to strate-gic experiments because more is unknown ratherthan known - the winner is often the one wholearns and adapts the quickest (Govindarajanand Trimble, 2005).

We agree with (Brown, 2009) that movementis primal and accompanies all the elements ofplay we are examining. Through movement play,we think in motion - movement structures ourknowledge of the world, space, time, and our re-lationship to others (Brown, 2009).

The creative person can be seen asembodying or acting as two charac-ters, a muse and an editor... the museproposes, the editor disposes. The ed-itor criticizes, shapes, and organizesthe raw material that the free playof the muse has generated. -StephenNachmanovitch

Our exploration of future game positionstherefore must take into account piece movementthat is likely, critical, interesting, stress induc-ing/relieving, or otherwise ”lively”. Children atplay engage other children or contemplate waysto engage their playmates. We therefore desireto create a heuristic which playfully examinesthe future consequences of the transformation ofstress on the board, as the pieces move about orare constrained by objects on the board, such asblocked pawns or lower-valued enemy pieces.

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We begin our efforts by conceptualizing thebuilding of a principal variation two moves intothe future, by first examining the single movethat creates the most perceived stress for our op-ponent (or mitigates the perceived stress causedby his pieces). We then look at the most likelyresponse. For Roos and Victor, the first thingwe do with play is to actively construct what wesee in our imagination. This construction phaseallows us to bring our intuition from all our expe-rience and our analyses into something concrete,something we can play with (Roos and Victor,1998). For de Geus (de Geus, 2002), we do notnavigate to a predefined destination. We takesteps, one at a time, into an unknowable future.

After ”sliding forward” in this fashion, wethen work backwards in our principal variation,examining the consequences of the next mostlikely move, and so on. In this ”serious play”we seek serious strategy (Roos and Victor, 1998)- we strive to retain control over the course ofthe imagined interaction by constantly reactingto its emerging results - what can and cannotbe done must depend on what the enemy can orcannot do (Luttwak, 2001). The success of anystrategic move always depends upon the currentinitiatives of and potential reactions available tocompetitors (Fahey, 1998). The ambiguity weface as we look into the future generates its ownpossible resolution (Byers, 2011). Any specificunderstanding of ambiguity must necessarily betentative - ambiguity is real but cannot be madeprecise. It is ambiguity and not certainty thatbest describes the way things are (Byers, 2011).

Play is experimenting with a toythat the player accepts as represent-ing his or her reality. This makesthe toy a representation of the real

world with which the learner can ex-periment without having to fear theconsequences... Underneath all thefun there is a very serious purpose:playing with one’s reality allows oneto understand more of the world welive in. To play is to learn. -Arie deGeus

Byers declares that the clarity of science hasroom within it for the ambiguous and goes seri-ously astray when this ambiguity is unacknowl-edged (Byers, 2011). Further for Byers, thestatement of the fundamental ambiguity (such asthe principal variation we develop in attemptingto ”play” a game such as chess) gives us an in-sight into what is going on; at every level, thesame fundamental dynamic of ambiguity playsitself out (Byers, 2011). The results of scienceand the critical problems that we face demandthat we face up to uncertainty and ambiguity,no matter how stressful this is (Byers, 2011).

We establish a few simple rules for our se-rious play: we orient our diagnostic explorationefforts (initially) along the lines of improving thescore of the weakest, vital diagnostic test - thestrategic principle which enables us to do some-thing now by guiding our action and helping toallocate scarce resources (Gadiesh and Gilbert,2001). We perform a exploration ”cut-off” onlyafter we confirm that the position in question isresilient and the moves left unexamined are notthe most promising (and remain so), after per-forming a shallower exploration.

man is in his actions and practice,as well as in his fictions, essentiallya story-telling animal. He is not es-sentially, but becomes through his his-tory, a teller of stories that aspire totruth... I can only answer the ques-

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tion ’What am I to do?’ if I can an-swer the prior question ’Of what storyor stories do I find myself a part?’ -Alasdair MacIntyre

We seek to tell stories - narratives - whichreflect our values and which paint different fu-tures of how the driving forces might behave. Wepay attention only to what we think we need toknow (Schwartz, 1996). The events are madeinto a story by the suppression or subordina-tion of certain of them and the highlighting ofothers (White, 1978). Meaning, then rests notwithin the individual symbolic acts which pos-sess ”interestingness”, but within the episode it-self (Johnson-Cartee, 2005). Experimentationmay seem incongruent with sustainability. Butin a world whose only certainty is change, adapt-ing - at the proper scale and speed - is the onlymeans to sustain what we value (Thiele, 2011).

We must confront ourselves with at least acrude and basic version of what ultimately mighttranspire, in order for decisions made now to be-come effective later. What seemed like a goodidea initially might not seem so when one looksat the consequences of the consequences. Us-ing a range of different scenarios you greatly re-duce the likelihood of unintended consequences(Ogilvy, 2002). In order to interpret presentmeaning, we need to spin out alternative sce-narios of future use. As only a snapshot ofthe present, current-position data is ambiguous.Many scenarios are necessary to interpret theseveral possible meanings of these signs (Ogilvy,2002). Unexpected discoveries in the principalvariation will cause the machine to re-focus itsefforts on the next most promising lines. Wethen begin to deepen our diagnostic explorationefforts and spend more time exploring alternatemoves in our principal variation. We do things

in order to discover what to do - our actions,which amount to little ”bets” on which movesare promising, produce insights which can be an-alyzed (Sims, 2011).

This is nothing more than Ashby’s model foradaptiveness (Bertalanffy, 1968), where the sys-tem tries different ways and means, and eventu-ally settles down in a field where it no longercomes into conflict with critical dynamic val-ues of the environment. Our leverage for deal-ing with ”driving forces” comes from recogniz-ing them, and understanding their effects. Lit-tle by little, our actions contribute to new driv-ing forces which in turn will change the worldof the gameboard once more (Schwartz, 1996).On some level, all three layers of intelligence -action, strategy, and prediction - need to occursimultaneously to create a seamless sustaining ofcompetitive advantage (Rothberg and Erickson,2005).

Intelligence for a system with limited pro-cessing resources consists in making wise choicesof what to do next (Simon and Newell, 1976).There is no easy solution for complex problems.What there is instead is an obvious direction (forexploration). The reason is that often there aretoo many (interacting) variables in a situation(Trout, 2008). This directed and flexibly persis-tent ”evolution” creates designs, or more appro-priately, discovers designs, through a process oftrial and error (Beinhocker, 2007).

Evolution is a general-purpose andhighly powerful recipe for finding in-novative solutions to complex prob-lems. It is a learning algorithm thatadapts to changing environments andaccumulates knowledge over time. -Eric Beinhocker

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Evolution is a possibility generator (Beck-ham, 1998). A variety of candidate designs arecreated and tried out in the environment; de-signs that are successful are retained, replicatedand built upon, while those that are unsuccess-ful are discarded (Beinhocker, 2007). Evolutionis a method for searching enormous, almost in-finitely large spaces of possible designs for thealmost infinitesimally small fraction of designsthat are ”fit” according to their particular pur-pose and environment (Beinhocker, 2007).

Evolution is a general-purpose and highlypowerful recipe for finding innovative solutionsto complex problems (Beinhocker, 2007). It is alearning algorithm that adapts to changing envi-ronments and accumulates knowledge over time(Beinhocker, 2007). The limits to this approachare seen to be the ability to manage complex-ity, and knowledge (Beinhocker, 2007). Beckhamagrees (Beckham, 2006), declaring that smart or-ganizations subject their most important deci-sions to a Darwinian environment in which thestrongest ideas survive and evolve to higher lev-els of fitness. The strategist looks at evolutionnot so much in terms of the survival of actual or-ganisms, but the survival of ideas (van der Heij-den, 2005).

Stephen Gould (Gould, 1996), speaking ofbiological evolution, notes that a species canevolve further only by using what physical prop-erties it has in new and interesting ways. Any bi-ological adaptation also produces a host of struc-tural by-products, initially irrelevant to the or-ganism’s functioning but available for later co-optation in fashioning novel evolutionary direc-tions. Evolution continually recycles, in differ-ent and creative ways, many structures built forradically different initial reasons (Gould, 2002).For Gould, much of biological evolution’s cre-

ative power lies in the flexibility provided by thisstorehouse of latent functional potential. It isquirky shifts and latent potential, redundancy,and selected flexibility - three basic principleswhich define and permit the creativity of evolu-tion, the capacity to originate novel structuresand functions.

For Mitchell (Mitchell, 2009), the result ofevolution by natural selection, in our case simu-lated, is the appearance of ”design” but with nodesigner. We hypothesize with Mitchell that theappearance of computer-produced design comesfrom chance, the selection for exploration of thepromising moves which are fit for the game envi-ronment, and long periods of simulated time inorder to validate this fitness.

We see the diagnostic exploration ”tree”formed in this fashion as an extended diagnostictest of how resilient and adaptively controllingour position is - the predisposed capacity to re-spond effectively to future situations that are be-yond our ability to predict. We see resilience asthe basic strength and adaptive control (with theflexible persistence of Beckham (Beckham, 2002)as a foundation) as the primary objective. Theseproperties are more measurable and meaningfulthan estimates of winnability, especially in thecase where we are deciding what to do next (andignorant of what the future holds). The ”tree” ismore a tool which is useful to plan what we wantto learn, rather than an expectation of where wewill be in the end (Cohn, 2006). We fully ex-pect that our opponent will (eventually) play amove which will take us outside of our currentlearning tree, and we fully expect, through themechanisms of resilience and adaptive control, tobe able to meet the challenges of the positionswhich newly emerge.

After ”evolving” a plan through a mecha-

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nism that ”proposes” and then ”disposes”, wecan test it using the principles of war gamingdeveloped by Gilad (Gilad, 2009). More specif-ically, we develop basic scenarios that illustratethe full range of potential strategic shifts (threatsor opportunities) (Page, 1996). A wargame de-velops scenarios (through the mechanism of sim-ulated competition) that otherwise might not oc-cur to us (Herman et al., 2009). The basic aimof a war game, which ideally captures the com-plexity of competitive dynamics, is to turn infor-mation into actionable intelligence (Fleisher andBensoussan, 2007). Gilad would have us envisionany and all plans that we develop as bets thatcome with risk, a risk originating from the com-petitive dynamics in our environment. We nowtest our plan and its assumption that the com-petitive response we will receive from our oppo-nent is containable. War gaming is nothing morethan role-playing in order to understand a thirdparty, with the goal of answering: What will theopponent do? What then is my best option? Gi-lad cautions that war gaming will not guaranteesuccess - nothing will - but states that it will in-crease the odds in our favor. Ideally, an effectivewar game produces a list of improvements for theexisting plan, or a list of options for a new plan.

Scenario-based planning attempts to makesense of the situation by looking at multiple fu-tures, which are treated as equally plausible, re-flecting not only the inherent uncertainty in thesituation, but also what is considered predictable(van der Heijden, 2005). The purpose of scenar-ios, wrote Pierre Wack, is to gather and trans-form information of strategic significance intofresh perceptions. When this works, it leadsto strategic insights beyond the mind’s previ-ous reach (Schwartz, 1996). For Schwartz, it isdriving forces, predetermined elements, and crit-

ical uncertainties which give structure to our ex-ploration of the future (Schwartz, 1996). Theprocess of building scenarios starts with look-ing for driving forces, the forces that influencethe outcome of events. Driving forces are theelements that move the plot of a scenario, thatdetermine the story’s outcome. Without drivingforces, there is no way to begin thinking througha scenario. For Schwartz, they are a device forhoning an initial judgment, for helping to decidewhich factors will be significant and which fac-tors will not (Schwartz, 1996).

For Michael Howard, it is essential that weconstantly try to adapt ourselves to the unpre-dictable, and to the unknown. Our plans, what-ever they are, are likely wrong. This fact is, forHoward, amazingly irrelevant. What matters isthat we get them right when the critical mo-ment arrives (Howard, 1974). We affirmativelyanswer Herman’s central question (Herman etal., 2009): if we had the opportunity to probethe future, make strategic choices, and view theconsequences of those choices in a risk-free en-vironment before making irrevocable decisions,that we would in fact take advantage of such anopportunity. For (Oriesek and Schwarz, 2008),wargaming is a form of accelerated learning.

This process is termed ”path analysis” byBossel (Bossel, 2007), who suggests that our firsttask consists of quickly finding the most relevantdevelopment paths despite a multitude of uncer-tain, time-dependent, or adjustable parameters.The efficiency of this task, in his and our opinion,depends on how cleverly possible parameter con-stellations are combined in consistent and plau-sible scenarios.

The second task of path analysis is the com-parative evaluation and assessment of differentdevelopment paths to clarify which path (or

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which group of paths) should be preferred. ForBossel, in this phase of the work, evaluation cri-teria have to be introduced that reflect the ex-istence and development interests of the system.We must make sure that the necessary minimumlevel of orientor fulfillment is achieved for eachindividual orientor, then we must determine thetotal quality of orientor satisfaction (for individ-ual orientors and some aggregated quality mea-sure).

We additionally note positions where imbal-ances are created (using our vital diagnostic in-dicators) and investigate the consequences, espe-cially when efforts to return to a resilient positionrequire extra efforts.

For software testing and configuration pur-poses, we envision the use of automated tour-naments of hundreds of games, each lasting per-haps three minutes long, to assess and fix the pa-rameters of these orientation/evaluation effortsso that we might succeed in the widest numberof situations. We envision a tool which identifiesand stores positions where faulty analysis wasgenerated. We see the programmer/developerexamining these saved positions and identifyingthe reason for the failure to orient/evaluate theindicated position.

We recognize certain positions as ”tacti-cal” in nature when responses become forced orwhen imbalances in vital indicators create fewbranches in our principal variation. We defer inthese cases to a methodology designed for a moretactical situation.

We critically examine the trade-offs betweenexamining principal variations that are manymoves long, versus the exploration of the sec-ondary and tertiary lines that do not go as deep.We conceptualize our machine behaving like achild at play, creating novel combinations, and

finding or discovering what works and does notwork in an evolutionary fashion.

We can base our efforts on the ob-served behavior of large groups of Internet-connected humans examining a common chessposition, such as the daily chess puzzle featuredat http://www.chessgames.com/index.html (wehave no connection to the owners of this site -one of us (JLJ) pays a yearly fee to access cer-tain advanced site features).

19 John Boyd’s OODA Loop

The OODA Loop (Observe, Orient, Decide,Act) is a strategic methodology which wasoriginally applied by USAF Colonel JohnRichard Boyd to the combat operation pro-cess http://en.wikipedia.org/wiki/OODA loop.Boyd was of the opinion that without OODAloops, we will find it impossible to comprehend,shape, adapt to, and in turn be shaped by an un-folding, evolving reality that is uncertain, ever-changing, and unpredictable (Boyd, 1996). Boydadvocates an approach of pulling things apartand putting them back together until somethingnew and different is created (Boyd, 1987). Fur-ther, Boyd suggests we present our opponentswith ambiguous or novel situations in which theyare not capable of orienting their behavior orcoping with what’s going on (Boyd, 1987), whilewe maintain our fingerspitzengefuhl. For Boyd,orientation shapes the way we interact with theenvironment, and therefore the way we observe,decide, and act (Boyd, 2005). Boyd suggeststhat effective orientation demands that we createmental images, views, or impressions, hence pat-terns that match with the activity of our world(Boyd, 2005).

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http://en.wikipedia.org/wiki/OODA_loop


For Boyd, in a competitive encounter againsta talented opponent, our limited perceptionscause novelty to be produced continuously, andin an unpredictable manner. In order to main-tain a competitive position we must match ourthinking and doing, hence our orientation, withthat emerging novelty. Yet, any orientation weassume prior to this emerging novelty is perhapsmismatched after the fact, possibly causing con-fusion and disorientation. However, Boyd pointsout, the analytical/synthetic process permits usto address these mismatches so that we can com-petitively rematch ourselves and thereby reorientour thinking and action with that novelty (Boyd,1992).

We therefore envision our diagnostic explo-ration process as an operational realization ofthis concept. We observe information, unfoldingcircumstances and interactions, orient our be-havior according to Bossel’s concepts discussedearlier, decide which path to explore, and thenact by ”sliding forward” one move. We then re-peat the process, periodically ”backtracking” toexamine moves which were initially determinedto be the next best.

(Boyd, 1976) attempts to philosophically ar-rive at a theory useful for conducting warfareor other forms of competition, such as playinga game. Boyd concluded that to maintain acompetitively effective grasp of reality one mustoperationally follow a continuous cycle of inter-action with the environment oriented to assess-ing its constant changes. Boyd states that theOODA decision cycle is the central mechanism ofsuch adaptation, and that increasing one’s ownrate and accuracy of assessment (compared tothat of one’s opponent) provides a strategic foun-dation for acquiring an operational advantage ina dynamically changing environment.

Conceptually, we are exploring the presentand future consequences of the transformationof positional stress, with an emphasis on thesustainability of the intermediate positions, thesatisfaction of our operational needs, and (ul-timately) the perceived winnability of the finalposition. We are faced with a dynamic, novel,unstable world that we must constantly adaptto even as we try to shape it for our own ends(Hammond, 2001).

20 Adaptive Campaigningmodel of Grisogono andRyan

Grisogono and Ryan (Grisogono and Ryan,2007) propose the model of Adaptive Campaign-ing as a modified form of Boyd’s OODA loopthat presents a more relevant form for the chal-lenges of operating in an environment with highoperational uncertainty. Here we ’adapt’ theirapproach for game theory.

Adaptive Campaigning proposes a repeat-ing cycle of Act Sense Decide Adapt (ASDA).By placing ’Act’ first this model stresses theneed to act (make exploratory trial moves) withwhatever information is present, and by imme-diately following that with a ’Sense’ of what haschanged in our environment. The ’Decide’ func-tion follows to determine what is learned fromthe sensed feedback that results from the ac-tion, and what to do next - including possiblere-orientation based on results from the vital di-agnostic tests.

These first three elements of Adaptive Cam-paigning correspond closely to the four elementsof Boyd’s OODA loop, but with a different em-phasis on where the cycle starts, and with the

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’Orient’ function of OODA incorporated into the’Decide’ functions of ASDA. The object of the’decision’ is to choose the next trial move in ourforward exploration, or to begin backtracking byexploring alternative moves in our principal vari-ation. So ’Adapt’, the fourth element of ASDA,explicitly adds the need to invoke adaptation andconsider what, if anything, should be changed onevery cycle, before continuing to the next cyclewith another external ’Act’.

Ideally, successful application of the ’Adapt’element results in the machine improving its abil-ity to focus/orient its efforts on the right objec-tives at the right time and in the right place.Modern combat, including game playing, cantherefore be characterized as competitive learn-ing in which all sides are constantly in a pro-cess of creating, testing and refining hypothesesabout the nature of the reality of which they area part (Kelly and Brennan, 2009).

Recent criticism of Adapting Campaigning(Thomas, 2010) claims that Boyd’s work ade-quately addresses the issues in question, andshould be revisited. Time will tell whetherOODA or ASDA loops will prevail.

21 Bent Flyvbjerg’s ”OODALoop”

Flyvbjerg (Flyvbjerg, 2001) has arrived at aOODA-type loop by asking the following ques-tions: 1. Where are we going? 2. Who gains,and who loses, by which mechanisms of power?3. Is it desirable? 4. What should be done? -which perhaps allows a more incremental or con-templative action than that suggested by Boyd.A sensitive perception of the power relations(and how they change) might allow one to ”feel”

how the situation might evolve. What Bourdieu(Bourdieu, 1990) calls the ”feel for the game”is central to all human action of any complex-ity, including planning, and it enables an infinitenumber of ’moves’ to be made, adapted to theinfinite number of possible situations, which norule maker, however complex the rule, can fore-see (Flyvbjerg, 2004).

When combined with a move-suggestionheuristic which is reasonably effective (such asthe satisfaction of sustainability needs), perhapsall that needs be done is to sit and execute.Flyvbjerg (Flyvbjerg, 2004) would have us ask”What possibilities are available to change ex-isting power relations?” There can be no ade-quate understanding of planning without plac-ing the analysis of planning within the contextof power. Rationality without power spells irrel-evance (Flyvbjerg, 1998b) (Flyvbjerg, 2004).

22 Endpoint Evaluation

Much as an employee receiving a yearly evalua-tion from his or her employer, we must come upwith a method to decide how desirable a posi-tion is, at the point we stop diagnostic explo-ration and probing efforts. But the future isunknown, and unknowable. Worse, selecting apoint at which we can evaluate, once and for all,the consequences of an action is a convenient fic-tion. In reality, the game positions we addressas outcomes are never really endpoints - theyare artificially imposed milestones (Watts, 2011).Something always happens afterward, and whathappens afterward is liable to change our per-ception of the current outcome (Watts, 2011).We seek therefore to establish dynamic potentialthrough a sum of lagging and leading indicators- the orientors discussed earlier, except that we

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are no longer interested in guiding diagnostic ac-tion but instead in establishing value, much asa Consumer Reports magazine evaluates, thenranks automobiles via a score relating to theirperceived value.

What do we choose to value? In our view,no term offers more promise than health (New-ton and Freyfogle, 2005), which connotes a kindof vigorous prospering. Health is an attribute,not of an entity in isolation, but of an entity in-tegrated into an environment. Health needs toinclude healthy relationships, cycles, and func-tions. Properly grounded, health can serve asour overall goal. In an interlocked system at agiven time, it is possible to maximize only onevariable (Newton and Freyfogle, 2005). We can-not, as David Ehrenfeld has observed, make ev-erything ”best” simultaneously. Health is plainlya goal (an end) rather than a means (Newtonand Freyfogle, 2005). The yardstick of successfor Hart (Hart, 1991) is the degree of freedom ofaction one enjoys at the end of the maneuver pro-cess. To this end one seeks all possible means ofkeeping the enemy guessing - the advantage goesto the side which can most quickly adjust itselfto the new and unfamiliar environment and learnfrom its mistakes (Howard, 1974).

What specifically do we choose to value?Whatever indicates or hints at how the presentinterlocking forces will resolve in the unknowablefuture. We value the signs of a healthy position,in the hope that this appearance of health re-flects (and is part of) a true health underneath(Foucault, 1994). These signs are both objectsof knowledge and that which they signify (Fou-cault, 1994). But why value a sign of health?We have to stop analysis somewhere - each signis just a surface phenomena and in itself not thething that presents itself to interpretation, but

instead the interpretation of yet other signs (Fou-cault, 1964). Semiotics is the theory of signs, ofhow they signify and mean what they mean. Wevalue signs because in playing a game we are -and become - the results of our dedication to ourchosen symbols (Ogilvy, 2011). We cannot knowwhat reality is in any absolute or objectivist fash-ion; instead, all we can know is our symbolic con-structions, the symbolic realities that are definedby our particular paradigms or frames of vision(Ogilvy, 2011).

Where possible, our numerical health scoreis based on chances of winning. In certain cases,opening book databases can be consulted to es-tablish a winning percentage, based on the num-ber of high-level games played and the win-loss-draw results. We speculate that two computerchess programs, each developed independently,might consistently arrive at nearly the same nu-merical endpoint evaluation, in the opening stageof the game, if calibrated to the winning per-centage expected from databases of recent high-level games, and where an identical strategy hasbeen selected of obtaining a resilient positionand adaptive control in the face of uncertaintyand resistance. Evidence for independent devel-opment might only be proven with longer timecontrols, such as in correspondence chess, or inpositions obtained in middlegame or endgame,where the different diagnostic exploration mech-anisms are uniquely influenced and differentiatedby finding sustainable paths to advantage.

Alternatively, distance (in moves) fromcheckmate can be used, where we can directlyperceive the checkmate in our diagnostic explo-ration efforts.

We suspect that most positions faced by ourmachine will not fall into either category. Wepropose instead a method which uses oriented

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stress to establish the size of the advantage, mea-sured as the estimated size of the mistake whichcan be made by player with the advantage, whichwould lead to a sustainable, even game. This in-dicator is more directly measurable than winningchances, which are often shrouded in dynamiccomplexity, and can be used in a game strategywhich seeks to accumulate small positional ad-vantages over time. What we are saying is simplythat it is easier (in most cases) to measure andfavor ”increasing distance from draw” than ”de-creasing distance from checkmate” - this alignswith Lawrence (Lawrence, 1997), who declaresthat it may be more important to know whetherwe are making progress towards the goal than itis to know the size of the gap between the cur-rent situation and the (ultimate) goal we haveset. We hypothesize that this conceptual foun-dation is equivalent, in most cases.

This measurement philosophy will need tobe adjusted in certain well-known cases, such asRook and pawn endings, or Bishop of oppositecolor endings, where an additional pawn mightnot have direct leverage into winning potential.Such cases would need to be programmed in on acase by case basis, starting with the most likelyendgames, and consulting a reference such asFine (Fine and Benko, 2003).

The purpose of the endpoint evaluation (forthe principal variation) should be to establisha marker against which we compare competingmoves. We construct strategic challenge lines(with less effort in time) and see how close wecome to the marker score. Those challenge lineswhich come close in score to the marker will be-come strategic fallback positions, and will be-come elevated to the new principal variation - ora replacement branch of the principal variation -if discoveries are made which force us to change

our mind on which move is the most promising.The details need to be fixed through procedureswhich are developed and refined in diagnostictournaments of hundreds of 3-minute games.Obviously, we do not want to spend time (orattention) looking at unpromising moves whichhold little chance of becoming the principal vari-ation.

In comparing different paths of system de-velopment, we hypothesize with Bossel that themost favorable path will be the one for which (1)the minimum conditions are always satisfied forall orientors, and (2) the overall orientor satis-faction is better (Bossel, 2007).

23 Complexity

We insist that it is complexity itself which de-mands an approach much like the proposedheuristic in order to play a game like chess in atactically empty position. Complex systems arecontrolled by countless individual interactionsthat occur inside the system (Benyus, 2002).The complexity present when playing in the po-sitional style is due to connections - the moreconnected something is, the more complex it is(Beckham, 2001). A change in one connectedthing gives rise to changes in the various thingsto which it is connected. More connections meanmore change (Beckham, 2001).

In a complex environment, the changes thatone action will generate are often beyond predic-tion because of all the other interactions theyset off (Beckham, 2001) (Byers, 2011). Smallchanges often amplify to become very largechanges - all we can do is watch for warning signs(Benyus, 2002). Complex conditions demandcontinuous adaptation. In a complex, highly

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connected system, things happen fast - or in away that involves a quick emergence into our per-ception. Maintaining a steady state of dynamicbalance requires continuous adjustment and ac-commodation. These shifts occur naturally asone change sets off another (Beckham, 2001).

In Beckham’s ”zone of complexity” muchdifferent approaches are needed to succeed.These approaches involve making short predic-tions, enabling self-organization, using simplematerials as building blocks, being continuouslyflexible and adaptive, all while looking for lessonsand metaphors in other complex systems, partic-ularly biological systems. Out there in the zoneof complexity, things are different. We agreewith Beckham that management that succeedswill be catalytic, facilitative, enabling, adaptive,incremental, and patient (Beckham, 2001).

Systems expert Russell Ackoff once empha-sized that success with a true system demandsthe effective management of interactions, notthe management of actions. Interaction is whathappens continuously at the various connectionsbetween things. It follows then that successfulmanagement in a densely connected system in-volves managing effectively in an environment ofcomplexity (Beckham, 2001).

24 Uncertainty

van der Heijden’s insightful observations of or-ganizations facing their future can be applied togame theory. In playing a game, complexity anduncertainty are unavoidable, and are perhaps themain challenges faced by the players (van derHeijden, 2002). To deal with complexity anduncertainty, game players develop thinking ap-proaches that are often flawed (van der Heijden,

2002). What is essential to long-term survivalis the ability to recognize and react to changebefore your opponent (van der Heijden, 2002).

All strategic decisions are affected by uncer-tainty and the further one peers into the future,the greater the uncertainty impacting decisions(van der Heijden, 2002). Uncertainty is not, ac-cording to Pierre Wack, ’just an occasional, tem-porary deviation from a reasonable predictabil-ity; it is a basic structural feature of the... en-vironment’. There can be no competitive ad-vantage or strategy without uncertainty (van derHeijden, 2002). The only solution according toWack, is to: ’accept uncertainty, try to under-stand it and make it part of your reasoning’,which is essentially what scenario planning at-tempts to do (van der Heijden, 2002).

The scenario planner observes from a pointin the future, from where the present is consid-ered and explained - as a historian would explainhistorical facts (van der Heijden, 2002). Becauseof inherent uncertainty, multiple future vantagepoints are required. From each position, a differ-ent story is told that makes sense of the current’blur’ (van der Heijden, 2002). Uncertainty en-sures that we will always end up with multiplescenarios: each one will be a logical story thatinterprets and explains what is happening andwhy (van der Heijden, 2002).

Complex systems carry a degree of intrin-sic unpredictability that cannot be reduced byany amount of analysis (van der Heijden, 2002).Managers need to embrace uncertainty, to thinkcreatively yet systemically about possible futureevents (van der Heijden, 2002). In doing so,scenario planners focus not on predicting sin-gle future outcomes, but rather on managing un-certainty in a number of scenarios projecting arange of plausible future outcomes (van der Hei-

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jden, 2002).

We embrace van der Heijden’s ideas, whichwe have liberally applied and directly quoted inthis section, in order to support our opinion thatother approaches to playing the game of chessare faced with a ’horizon effect’ that exists inpart due to a failure to address the full effects ofcomplexity and uncertainty.

25 Narrative Rationality

It is generally impossible to decide, at the timeof perception, whether perceptions will prove ac-curate or inaccurate, correct or incorrect, be-cause perceptions are partly predictions thatmay change reality, because different perceptionsmay lead to similar actions, and because similarperceptions may lead to different actions (Star-buck and Milliken, 1988). Many perceptual er-rors, perhaps the great majority, become erro-neous only in retrospect (Starbuck and Milliken,1988). Partly for this reason, we seek a narrativeversion of rationality.

To the extent that a story can betold about the world around us, sensecan be made of its complex relation-ships, and judgments can be leviedupon them. The mental acts of under-standing and judging, cognitive psy-chologists suggest, is achieved throughthe organization of perceptions intonarrative format, and, subsequently,the integration of newly acquired nar-ratives into available, already inter-nalized tales...

Narrative rationality (Fisher, 1985) is an at-tempt to recapture Aristotle’s concept of phrone-sis, or ”practical wisdom.” Practical wisdom

prompts us to address the question, ”And thenwhat?” before taking action (Thiele, 2011). Wedesignate this concept as the meta-paradigmwhich explains how a machine can follow ourhuman-written instructions to ”play” a gamesuch as chess. For Schank, storytelling andunderstanding are functionally the same thing(Schank, 1995). What is essential to narrationis not that it is a verbal act of telling, as such,but that it embodies a certain point (or points)of view on a sequence of events (Carr, 1991).

Louis Mink has called narrative a primary”mode of comprehension” and a ”cognitive in-strument” (Carr, 2001). Very simply, narrativeis the form in which we make comprehensiblethe many successive interrelationships that arecomprised by a path or progress through life orhistory (Mink, 2001). Narrative is a primary andirreducible form of human comprehension, an ar-ticle in the constitution of common sense (Mink,2001). The cognitive function of narrative formis not just to relate a succession of events, butto mentally give form or shape to an ensemble ofinterrelationships (of many different kinds) as asingle whole (Mink, 2001).

...This capacity arises because nar-rative, and narrative alone, allows usto forge a coherent temporal/historicalcontext for existence while makingsense, and justifying, actions in termsof plans and goals. -Leslie Paul Thiele

The narrative paradigm offers a reliable,trustworthy, and desirable guide to belief and ac-tion (Fisher, 1985). When narration is taken asthe master metaphor (Fisher, 1984), it subsumesthe others. The other metaphors are then con-sidered conceptions that inform various ways ofrecounting or accounting for choice and action.

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In short, good reasons (i.e., for playing one moveover another) are the stuff of good stories, themeans by which humans realize their nature asreasoning-valuing animals (Fisher, 1984).

There is no genre that is not an episode ina story (Fisher, 1985), which we stretch to in-clude the conflict-situation faced by players in agame. Good reasons (for making a move) are anexpression of practical wisdom; they are, in theirhighest expression, an encompassment of what isrelative and objective in situations. They func-tion to resolve exigencies by locating and activat-ing values that go beyond the moment, makingit possible that principles of decision or actioncan be generalized (Fisher, 1985).

No guarantee exists that one who uses nar-rative rationality will not adopt ”bad” stories,but it does mitigate this tendency (Fisher, 1985).The absence of narrative capacity or a refusalof narrative indicates an absence or refusal ofmeaning itself (Fisher, 1984). When placed inthe context of an episode (Frentz and Farrell,1976), symbolic acts (such as sequential moves ina game) acquire episodic force, which completesthe explanation by specifying the communicativefunction of the acts within the overall sequentialstructure of an episode. As stated earlier, theevents are made into a story by the suppressionor subordination of certain of them and the high-lighting of others (White, 1978).

The consequential force of any symbolic actoccurring in an episode follows logically fromthe episodic force of that act (Frentz and Far-rell, 1976) - in our case, the narrative-inspiredprincipal variation sets a ”marker” score whichdetermines the threshold of our attention whenconsidering other moves.

During the encounter, actors (in our case,the players in the game) will survey the prob-

able rules of propriety and - in principle - ex-clude the least likely candidates (Frentz and Far-rell, 1976). For (Frentz and Farrell, 1976), it iscontext (meaningfulness criteria and encounters),episodes (strategically generated sequences of ac-tion whose goals and form are conjointly createdby two or more actors) and symbolic acts (suchas imagined moves in a game) which togetherform a language-action paradigm of rationality.

We aim for narrative coherence (Carr, 1991),an essential structural feature in performing anaction, as we intend to shape and form futureevents. When plans go awry, when things fallapart, (Carr, 1991) it is by reference to or bycontrast with story-like projections, ”scenarios,”that they do so. What occurs ”one thing afteranother,” is, in terms of reality (Carr, 1991), theresult of narrative coherence. Narrative coher-ence (Carr, 1991) is what we find or effect inmuch of our experience and action, and to theextent that we do not, we aim for it, try to pro-duce it, and try to restore it when it goes missingfor whatever reason.

David Carr further informs us (Carr, 1991)that if we think of narrative as ”organizing,””making sense of,” and rendering ”coherent” ouraction and experience, narrative organization ofaction may be considered cognitive in the sensethat the action’s implicit ”story” is nothing butour knowledge of what we are about or whatwe are doing. Such narratives (Carr, 1991) mayserve to organize and make sense of the experi-ence and action of their authors and their read-ers, focusing their attention in certain directionsand orienting their actions toward certain goals.A good story - necessary in sensemaking - holdsdisparate elements together long enough to en-ergize and guide action (Weick, 1995).

In the end, our machine-code (when exe-

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cuted) accomplishes what rational people seekin any generalized situation (Frentz and Farrell,1976): we consider various alternative actionsand examine their consequences by an imagina-tive rehearsal of episodes. In light of this re-hearsal and their intuitions about the proprietyof each form the episode might take, a partic-ular social action (here, a move in a game) ischosen. We aim for (Fisher, 1984) an inherentawareness of narrative probability, what consti-tutes a coherent story, and a constant habit oftesting narrative fidelity, whether the stories weexperience ring true with the value-inspired sto-ries we know to be successful in diagnostic tour-naments of many games.

A narrative which can bind the facts of ourexperience together leads to the full intelligibil-ity and expression of our abstracted rules, princi-ples and notions (Fisher, 1984) (Goldberg, 1982).Viewing events and actions in light of what fol-lows them, and of what follows from them, is ourway of viewing the present - more generally, it isour way of viewing time and living and acting init (Carr, 1991).

The story schema can be applied to almostall events in our social life (Polkinghorne, 1988).Mink wrote of the configurational mode of com-prehension, where things are understood as ele-ments in a single and concrete complex of rela-tionships (Mink, 1974). Configurational compre-hension emphasizes the relations that may holdbetween particular elements, and perhaps is crit-ical for any attempt to hold together a numberof elements in nice balance (Mink, 1987). Wetruly approach an ”artificial” intelligence whenwe can tell coherent stories about our presentposition and effectively determine a useful-for-future-maneuver adaptive capacity. A machinewhich executes diagnostic tests written by a pro-

grammer - the results of which are later used toguide coherent action - can appear ”intelligent”to those who are unaware of the actual heuristicsused.

26 Results

We have created software to demonstrate cer-tain features of the proposed heuristic and nowexamine four positions to see if we can obtaina better positional understanding of how wellthe pieces are performing. John Emms (Emms,2001), reached Figure 6 as white (black to move)with the idea of restricting the mobility of black’sknight on b7.

Figure 6: Emms-Miralles (Andorra, 1998) Constraint mapsLegend: The left diagram identifies the possible constraintsimposed by the white pieces, with red representing pawn con-straints, yellow minor piece constraints, green rook constraints,blue-green queen constraints, and blue king constraints. Theright diagram identifies possible constraints imposed by theblack pieces. The white and grey squares represent the stan-dard chessboard squares without constraints.

How fully engaged is this piece in the game?Let’s see what the influence diagram and simu-lation diagram from the proposed heuristic showus:

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Figure 7: Emms-Miralles Tracing knight mobility from b7-a5-c4-b2 and b7-d8-e6-g5

Figure 8: Emms-Miralles Influence Diagram and SimulationDiagram for Nb7

We generate the constraint maps as in Fig-ure 6 in order to estimate the squares that theknight on b7 is likely to be denied access. Wethen apply the constraint maps to the individ-ual vectors which make up the influence diagramas in Figure 7 to create the simulation diagram.When a movement vector hits a constraint, fu-ture mobility through that square is constrained,and we use an ”X” to indicate constrained mo-bility. We can see from the X’s (denied potentialmobility) of Figure 8 that the movement of thepiece on b7 has been constrained. It is Emms’view that positional details like this one can bevitally important when assessing positions.

Figure 9: Constraint maps, white (left), black (right),Estrin-Berliner variation analysis (1965-68 corr.) after 12.Qe2Be6 13.Qf2, Black to move

Figure 10: Influence Diagram and Simulation Diagram forBc1

Figure 11: King safety heuristic maps: left - black kingsafety, right - white king safety. In the left diagram, darkersquares are safer squares for the black king, while lighter col-ored squares are more dangerous.

The organization and its environ-ment impinge on each other in many

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ways. Strategy succeeds or fails by in-teracting with this environment. Itsucceeds by avoiding, making use of,or overcoming, the impingements. -Geoffrey Chamberlain

Figure 9 examines a sideline from Estrin-Berliner (1965-68 corr.) after the proposed im-provement 12.Qe2 Be6 13.Qf2. How fully en-gaged is the white Bishop on c1? We generatethe constraint maps and influence diagram asbefore in order to construct the simulation di-agram. We see that the bishop on c1 can enterthe game after moving a pawn out of the way,and become useful for creating and mitigatingstress in future positions.

Figure 11 displays an experimental kingsafety heuristic which is generated from all thepiece influence diagrams and a rule which awardspoints based on number of pieces which can at-tack a square and the distance/constrained effortrequired to do so.

Figure 12: Constraint maps, white (left), black (right),Umansky-World correspondence game (2009)

Figure 13: Influence Diagram and Simulation Diagram forQe8

Figures 12 and 13 examine a positionfrom the recent Umansky-World correspondencegame. The constraint map gives insight to thecontrolling influences present on the squares, andthe influence diagram/ simulation diagram forthe Queen on e8 gives insight to what this piececan threaten in 3 moves. Note that this piececan influence square c1 via the difficult to findmove sequence e8 to e6-h6-c1.

Figure 14: Influence Diagram and Simulation Diagramfor Rb8, Levy-Chess 4.4, simultaneous exhibition, 1975, after27.axb5

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Figure 15: Influence Diagram and Simulation Diagramfor Rb8, Levy-Chess 4.4, simultaneous exhibition, 1975, after31.Bc8

Figures 14 and 15 show how a machine canpotentially recognize a trapped piece, with anexample first identified and discussed by (Levy,1976).

The computer can use the heuristic knowl-edge present in the influence diagram and simu-lation diagram to estimate the strategic potentialor how fully engaged each piece is in the game.The maps are a useful holistic measurement of acapacity to produce stress in a position, and canbe used as part of an oriented, vital system-levelindicator to predict and manage the sustainabledevelopment of a position in a chess game. Per-haps sensemaking and noticing interact as com-plements in effective problem solving: sensemak-ing focuses on subtleties and interdependencies,whereas noticing picks up major events and grosstrends (Starbuck and Milliken, 1988). Noticingdetermines whether social actors even considerresponding to environmental events. If eventsare noticed, actors make sense of them; and ifevents are not noticed, they are not available forsensemaking (Starbuck and Milliken, 1988).

A system that is to control its environmentsuccessfully must adapt by constructing modelsthat allow it to decide what information to get,and how to act on it (Lloyd, 1995). To solve

problems of control and stability, one needs apicture of the qualitative behavior of the system.That is, for nonlinear systems, control requiresinsight into the nature of the system’s dynam-ics (Lloyd, 1995). To characterize and controlour surroundings, we must identify the parts ofthe system where order can be increased at theexpense of disorder (Lloyd, 1995).

27 Conclusions

The elements of a system and theirinteractions define the system struc-ture...

Alternative conceptual frameworks are im-portant not only for further insights intoneglected dimensions of the underlying phe-nomenon. They are essential as a reminder ofthe distortions and limitations of whatever con-ceptual framework one employs (Allison and Ze-likow, 1999). Only by analyzing a phenomenonfrom an alternative perspective (preferably mul-tiple alternative perspectives) can all the intri-cacies of a situation be understood (Canonico,2004). Our alternative conceptual frameworkfor machine-based chess can, at minimum, al-low us deeper insight and better understandingof current methods. Particularly in explainingand predicting actions, when one family of sim-plifications becomes convenient and compelling,it is even more essential to have at hand one ormore simple but competitive conceptual frame-works to help remind us of what was omitted(Allison and Zelikow, 1999). To solve problemsthat blind spots have made unsolvable, peopleneed new perceptual frameworks that portraythe problematic situations differently (Starbuckand Milliken, 1988). Allison and Zelikow believethis is a general methodological truth applicable

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in all areas of life, including, in our opinion, astrategy for playing a game.

...By answering the basic ques-tions about space, time and structure,we describe the conceptual model ofthe system... Creating a conceptualmodel... very much resembles that ofperception -Alexey Voinov

Where meaning is concerned, it is not amatter of converging on closer and closer mea-surements - alternative contexts can determinewidely divergent significances for the same phys-ical entity (Ogilvy, 2011). Rival interpretationswill continue to contest the proper reading ofwhatever evidence is brought to bear (Ogilvy,2011). One source suggests that we should lookat between four and six alternate concepts forour design (Kossiakoff and Sweet, 2003).

We agree with strategist Bernard Brodiethat strategy is a field where truth is soughtin the pursuit of viable solutions, not at all likepure science, where the function of theory is todescribe, organize, and explain and not to pre-scribe. The question that matters in strategyis: Will the idea work? (Steiner, 1991). Brodiebelieved that strategy was associated with prob-lems involving economy of means, i.e., the mostefficient utilization of potential and available re-sources (Steiner, 1991).

A systemic (rather than analytic) approach,focusing on interactions and feedback mecha-nisms rather than concentrating on agents, willoffer insights on where to apply leverage so asto contribute to the development of security andstability. The targeting derived from such an ap-proach will focus on building and fostering iden-tified sources of resilience and adaptive capacity,while mitigating or disrupting sources of stress.

Complexity theory highlights the non-linearityof feedback mechanisms, implying a requirementfor the continuous monitoring of measures of ef-fectiveness in order to adapt effects-seeking op-erations (Calhoun and Hayward, 2010).

The properties of the parts can beunderstood only from the dynamics ofthe whole. In fact, ultimately thereare no parts at all. What we call apart is merely a pattern in an insep-arable web of relationships. -FritjofCapra, The Role of Physics in theCurrent Change in Paradigms

Ecosystems are working models of sustain-able complex systems, and it is reasonable tostudy them for clues to the sustainable manage-ment of the human enterprise (Jorgensen andMuller, 2000), including ’conflict ecosystems’mentioned by Kilcullen (Kilcullen, 2006). Weidentify systems thinking and the systems ap-proach as the theoretical basis for an orienta-tion/evaluation methodology, shifting our focusfrom the parts to the whole. The use of ap-proximate knowledge and the conceptualizationof a network of interacting components is real-ized through a system dynamics model of stress,or positional pressure.

The reality of the position on the chess-board is seen as an interconnected, dynamic webof power relationships, with oriented, cumula-tive stress one driving force of change. Youcan avoid reality, but you cannot avoid the con-sequences of avoiding reality (Ayn Rand). Weseek resilient positions and flexible, adaptive ca-pacity (with the promise of sustainable develop-ment) to counter the effects of unknown posi-tions that lurk just beyond our planning horizon.The concepts of orientors and indicators, cumu-

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lative stress, constraints and virtual existence al-low us to effectively simplify the dynamic realityof each game piece interacting with every othergame piece on the board - to the point where wecan predict promising directions of exploration(via the mechanism of stress transformation) andidentify the accessibility space (Bossel, 1998) offuture sustainable development.

In the final analysis, perceptionseems to be the key to skill in chess...The difference between two players[when one defeats the other in a game]is usually that one looks at the promis-ing moves, and the other spends histime going down blind alleys. -NeilCharness, Chess Skill in Man andMachine, 1977

A model can be considered as a synthesisof elements of knowledge about a system (Jor-gensen and Muller, 2000). Our model of dy-namic interaction presented in this paper ideallycaptures the dominant variables that control thetransformation of stress (Kossiakoff and Sweet,2003), omitting the higher order effects that havea cost/benefit deemed to be overall not effective.No models are valid or verifiable in the senseof establishing their correctness (Sterman, 2000)(Voinov, 2008). The question facing clients, aca-demics, and modelers is not whether a model istrue but whether it is useful as a basis for someaction, which in our case, is orienting diagnos-tic exploration efforts (through the critical lines)in an exponentially growing tree of possibilities,in a way that obtains actionable intelligence andtherefore allows a strong positional game of chessto be played.

(Miller and Page, 2007) advise, with regardto computational modeling, that we judge the

quality and simplicity of the model, the clev-erness of the experimental design, and examineany new insights gained by the effort. We shouldalso ask ourselves if our model has just enoughof the right elements, and no more. To be agood model, Miller is of the opinion that we havestripped phenomena down to their essentials, yethave retained enough of the details to producethe insights we require.

Learning to handle a complex sys-tem means learning to recognize a spe-cific set of indicators, and to assesswhat their current state means for the’health’, or viability, of the system.Often this learning of indicators isintuitive, informal, subconscious... -Hartmut Bossel

For Nijhout et al., (Nijhout et al., 1997), themost important thing that should be required ofa model is that, with small quantitative changesin parameter values, it can produce the evolu-tionary diversity present in that pattern, andthe effects of perturbation experiments and mu-tations on the pattern. It must also reproducein its dynamics reasonable portions of the onto-genetic transformation that the real pattern un-dergoes (Nijhout et al., 1997). We conceptualizean equivalence with the game position, and theexploratory moves suggested by our model.

Ideally, our responsibility would be to usethe best model available for the purpose at hand(Sterman, 2000) despite its limitations. Weview modeling (Sterman, 2000) as a process ofcommunication and persuasion among modelers,clients, and other stakeholders. Each party willjudge the quality and appropriateness of anymodel using criteria which reflect on their roleand perceived future benefits. This includes thetime and effort involved in the unending strug-

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gle to improve the model to the point where itsperformance reflects what theory would expectof the particular approach. Modeling team Amight not want to use a particular model due tosignificant time, money, belief, performance, andfamiliarity with their current approach. Team Amight not even be interested in discussing newapproaches. However, modeling team B mightbe looking for a new challenge, perhaps due todissatisfaction with the current model, a belief inpredicted performance, or perhaps due to a will-ingness to spend long hours and to engage withthe types of problems suggested by the new ap-proach. Team A might now become interested,seeing the preliminary success of team B.

Our attempts to reengineer the way ma-chines play chess are, in the true spirit of reengi-neering (Hammer and Stanton, 1995), throwingaway current methods and starting over, butplacing at the forefront of our design efforts thevalues and concepts of positional chess and Sys-tems thinking. We acknowledge the dynamicand static elements of a chess position, and con-struct a sensor array which responds to a percep-tion of stress in the position in order to orient ourefforts to effectively navigate in an exponentiallygrowing diagnostic exploration effort. We adopta Soft Systems Methodology - that is, we see thegame position as complex and confusing, and weseek to organize the exploration of future conse-quences through the means of a learning system(Checkland and Poulter, 2006).

The proposed heuristic offers insight on theability of the chess pieces to create and miti-gate stress and aims for a rich awareness of dis-criminatory detail (Weick and Sutcliffe, 2007)between promising and less promising positions.We agree with Donohew, et al., (Donohew et al.,1978), that information seeking must be a pri-

mary method for coping with our environment.Key components include the monitoring of struc-tural tension created by the pieces as they mu-tually constrain each other and seek to satisfyvital system-level needs, and the attempt to cre-ate positions which serve as a platform for fu-ture success, in a future that is uncertain. Allsustainable activities have to accept the naturalsystem of constraints in which the investigatedentity operates (Jorgensen and Muller, 2000).

The invariance of basic orien-tors... as well as the change in at-tention focus resulting from changesin orientor satisfaction, provide thesystem with the ability to cope flexi-bly and adaptively with a widely andquickly changing state of system andenvironment. -Hartmut Bossel

Our orientation/evaluation centers on an ar-ray of vital diagnostic appraisals of the cumula-tive stress each side inflicts on the opponent’sposition, and the perceived mitigation of suchstress. (Selye, 1978) considers stress to be an es-sential element of all our actions, and the com-mon denominator of all adaptive reactions. Weaim to reduce our opponent’s coping ability andadaptive capacity through oriented targeting ofstress. The dynamic forces of change, acting overtime and in a future we often cannot initially see,ideally transform the reduced coping ability ofour opponent, our carefully targeted stress, andour resilient position full of adaptive capacity, tofuture positions of advantage for us. The entirepurpose of modeling stress is to aid the orienta-tion of diagnostic exploration efforts - that is, weorient exploration efforts in priorities based onthe changing amounts of stress in the position(and the results of vital diagnostic tests). Weadditionally monitor the stress that threatens

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to become real, having the property that (vonNeumann and Morgenstern, 1953) have called”virtual” existence. Even if the threat does notmaterialize, it nevertheless has the capability toshape and influence the events that do becomereal.

It is the possibility of letting agreat many relationships influenceeach other under precisely stated as-sumptions and of determining theconsequences, which gives the com-puter model its enormous power andadvantage over conventional planningmethods...

(Jorgensen, 2009) and (Bossel, 2007) discussthe application of Bossel’s orientor ideas to sim-ulated animals (animats) roaming in simulatedenvironments, where orientation rules are devel-oped over time to direct and control the behaviorof the simulated animal and optimize the acqui-sition of food and energy resources. These simu-lations involve the ’perception’ by the simulatedanimal of clues in the environment to the pres-ence of food as well as danger. We ask ourselveswhat orientation rules would develop if the sim-ulated environment were instead the board gameof interest. Might we then develop optimal rules(or minimally, a good set of rules) for orient-ing our diagnostic exploration behavior criticalin playing a board game?

We acknowledge that resilience is a distin-guishing characteristic of any successful system(Sanderson, 2009) (Gunderson et al., 2010). Thecreation of resilient positions full of adaptivecapacity allows us to sharply and effectivelypostpone diagnostic exploration efforts in less-promising lines with the low-risk promise of suf-ficient resources to ’MacGyver’ the unknown fu-ture that lies beyond. We determine the level

of resilience present in a position using a set of(heuristic) vital diagnostic tests, such as the onesproposed by Bossel. We desire a methodologywhich emulates a productive thinking process,such as one envisioned by (Hurson, 2008), butwhere we playfully consider responses that re-flect the changing, urgent stress in the position,and the resilience of the less urgent positions andanalysis lines left unexamined.

...The speed with which the greatnumber of calculations are accom-plished enables one to experiment re-peatedly with different assumptionsfor the future in different parts of themodel, i.e. with different ”scenar-ios”. - Michael G. Strobel and Hart-mut Bossel

We configure our scripts for diagnostic ex-ploration activity using the results from auto-mated tournaments of 3-minute-duration games.

From the highest level, we desire to modelthe cumulative dynamic stress present in theposition so that we can effectively explore thepossible directions of promising development.Our estimate of winning chances critically de-pends upon 1. exploring the promising and risk-mitigating paths and 2. correctly identifyingthose paths whose exploration of future conse-quences can justifiably wait until later. Inaccura-cies in these two areas of classification will createa limit to overall performance, as we strategicallyattempt to compete against other agents withdifferent and refined approaches to this sameproblem. We seek, as a strategy, to gain a sus-tainable edge over our opponent, and see thecareful formation and execution of the strategicplan as the best and most productive way to ac-complish this.

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The concepts of competitive intelligence,critical success factors, serious play, evolution,wargaming, Boyd’s OODA Loop, Grisogono andRyan’s Adaptive Campaigning Model, and end-point evaluation critically complete the concep-tualization. We seek to ”play” the game of chessthrough a strategic orientation and explorationthat is guided by a playful-but-serious examina-tion of the future consequences of stress trans-formation, the tentative separation of positionsinto categories of uninteresting, not worthy of at-tention, probably sustainable (allowing a halt tofurther explorations) and interesting, worthy ofattention, possibly unsustainable (requiring addi-tional time/diagnostic exploration), and vital di-agnostic tests which orient, summarize and sim-plify the complexity present on the game board.We gather competitive intelligence to measureour successful attainment of critical success fac-tors - our success or failure will serve as our guideto diagnostic action.

We establish value through an endpoint eval-uation which sums critical parameters in orderto 1) critically perceive the size of the mistakewhich would need to be made to reach a sus-tainable, even game, 2) accumulate small, sus-tainable positional advantages and 3) establisha marker to develop challenge lines with strate-gic potential if or when problems develop withbranches in our principal variation, or with theindicated move itself.

Serious play can leverage the accumulatedstrategic information and judgment gained overthe years. It can help develop original strategies(Roos and Victor, 1998). Serious play can en-able us to explore, challenge, disagree, and cometo agreement on how we will meet the future(Roos and Victor, 1998). We intelligently an-swer the question ’What am I to do?’ by using

our knowledge of the power relations and basicneeds to create stories - narratives - which as-pire to best play, helping to create sustainablepositions with a sustainability margin useful inprogressing towards our ultimate goal of winningthe game.

The presented results demonstrate the pos-sibilities of the proposed building blocks for fourtest positions. Perhaps chess is more than justcalculation (Aagaard, 2004), but the day maycome sooner than we think when computers useheuristics to play a positional game of chess atskill levels equal to their current strong tacticalplay. Correspondence chess would provide theideal testing ground for a positional heuristic.

The proposed heuristic offers promise as away to play the game of chess, precisely because1) it follows a strategy which addresses the com-plexity of the reality on the chessboard, 2) it de-velops scenarios which address uncertainty, re-sistance and sustainability, 3) actions taken bythe machine use competitive intelligence, powerrelations and leverage in diagnostic explorationswhich ultimately measure freedom of action and”mistake margin” from an even game, and 4)it follows Rumelt’s strategic approach of diag-nosis, guiding policy and coherent action. Cre-atively, we propose promising moves and thendispose of the lines which fail to grab our at-tention, proceeding in an evolutionary way toexplore a consequential space otherwise inacces-sible by brute force methods. We ultimatelychoose a move which is diagnostically fit for theenvironment, which is understood to be domi-nated by the consequences of the consequencesof the consequences of the power relations of thegame pieces.

We might borrow the words of economistJoseph Schumpeter (1883-1950) and theorize

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that chess is a game of Creative Destruction.

Future work will involve the construction ofa prototype software application which imple-ments the concepts discussed in this paper.

We close with a quote from Robert Bellah etal., in Habits of the Heart:

We hope the reader will test what wesay against his or her own experience,will argue with us when what we saydoes not fit, and, best of all, willjoin the public discussion by offeringinterpretations superior to ours thatcan then receive further discussion.

Note: colored diagrams were produced by a com-puter program in HTML format and rendered in a Fire-fox web browser in a method similar to that used by thesoftware program ChessDiagrams by Ambar Chatterjee.

Special thanks to all my friends at chessgames.com,

through whom I continue to learn about chess.

28 Appendix A: SelectiveSearch and Simulation

We recognize that the concept of selective searchis a critical concept in playing the game of chess,but we suggest an alternative way of thinkingabout the method where we choose to explorecertain future lines, and choose not to exploreothers.

The phrase dynamic simulation with strate-gic scenarios has certain advantages. First, werecognize that we are using a dynamic model.Second, the concept of a simulation permits usto think about or explore the uncertain futurewhere we encounter resistance. Third, we arestrategic in our selection and rejection of lines.

Last, we follow certain scenarios in our war gam-ing of the future - this allows us to learn whatmight lie ahead.

We suggest that this approach is more pre-cise and allows us to answer the question ”So,how are you doing selective search?” with theanswer, ”What we are doing is more than justsearching - it is more like conducting a compli-cated diagnostic test of how ’ready’ we are forthe uncertain future. As part of a strategy, weexplore the critical emerging results of stress in-teractions. We construct a dynamic model andcreate strategic scenarios. The process resemblesbiological evolution, as we first propose moveswhich satisfy orientors aimed at sustainability,and then dispose of lines judged by our compet-itive intelligence to be not worth our attention.

We aim for resilience, adaptive control andflexible persistence in the face of complexity andthe uncertain plans of our opponent. We developand expand scenarios which have strategic po-tential to become a replacement principal varia-tion (or replacement branches) when unexpecteddiscoveries are made.

Through endpoint evaluation we establisha marker which is used to set the threshold ofour attention when constructing challenge lines.Specifically, our attention is diverted away fromexploring those (unlikely) challenge lines wherewe have demonstrated sustainability and wherewe believe we have a margin which allows forfallback positions, if necessary. We aim to cre-ate results normally produced by a productivethinking process.”

This concept can be compared to the ideapresented in (Ward and Schriefer, 1998) of a dy-namic scenario generator. The authors note Pe-ter Senge’s observation that ”Perhaps the sin-gle greatest liability of management teams is

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that they confront complex dynamic realitieswith a language designed for simple static prob-lems”. Senge proposes that the basic purposeof a learning organization is to continually ex-pand and create its future. We concur, and agreewith Ward and Schriefer that both profoundand rapid learning occur when scenario planningand systems thinking are employed. The dy-namic scenarios methodology combines the twoapproaches. Today’s decisions and events takeon different meanings depending on the differenttomorrows that are their possible consequences(Ogilvy, 2011).

Simply put, we agree with Flyvbjerg (Fly-vbjerg, 2001) that rationality and power are in-terrelated, that in ”playing” a game our timeis best spent pursuing answers to the follow-ing questions (Flyvbjerg, 2001): What are themost immediate and the most local power rela-tions operating, and how do they operate? Howhas the active exercise of power in the relationsbeing investigated affected the possibilities forthe further exercise of power, with the result-ing reinforcement of certain power relations andthe attenuation of others? How are power re-lations linked together, according to what logicand strategy? How have these relations madecertain rationalities possible and others impossi-ble, and how do the rationalities support or op-pose the power relations? How can the gamesof power be played differently? Power is theprocess, which via struggles and confrontationstransforms, supports, or reverses these force re-lations (Flyvbjerg, 2001).

29 Appendix B: The Impor-tance of Sustainability

We have placed much emphasis on the concept ofsustainability, and feel the need to explain whythis concept is such a critical strategy when play-ing a game in the positional style.

Whatever diagnostic test we use for explor-ing the future cannot prepare us for all possibil-ities. We instead must be ”ready” for whateveremerges from the ”mess” of interactions, someof which are foreseeable and are representativeof the types of situations we will later face. Sus-tainability allows us to continuously generate re-sponses - future positions which in turn are like-wise sustainable. Anyone who has played com-petitive sports learns to develop quick tests todetermine, on the fly, whether the current teamposition is sustainable, and if not, what needsto be done (personally, or calling instructions toothers) to correct it.

When facing a tactically empty position, wefeel that a strategy that develops, then selec-tively expands a portfolio of likely scenarios isa good way to determine how ready we are toface an uncertain future. We prepare ourselvesto respond to the mistake of our opponent, orfor the situation where a scenario initially judgedto be not worth our attention, had unexpectedside effects which resulted a more favorable po-sition for our opponent. We seek to uncover un-expected situations ”down the road” which im-pact the ”health” and sustainability of the po-sition and cause us to shift our move played toone with a more favorable outlook. We are nowready in general, and will handle the specifics asthey come.

In short, we feel that the nature of the com-

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plexity which exists on the game board, of dy-namic and evolving systems in general and of’conflict ecosystems’ and the peculiarities of sys-tems in particular, must all be reflected in thesearch for general principles of sustainable de-velopment (Bossel, 2007).

30 Appendix C: Related Quo-tations

The analysis of general system principles shows thatmany concepts which have often been considered asanthropomorphic, metaphysical, or vitalistic are ac-cessible to exact formulation. They are consequencesof the definition of systems or of certain system con-ditions. - Ludwig von Bertalanffy

a good model enables prediction of the futurecourse of a dynamic system. - Bruce Hannon andMatthias Ruth

Perception, motivation, and values combine tocreate choice. - Joe Vitale

It’s your decisions about what to focus on, whatthings mean to you, and what you’re going to do aboutthem that will determine your ultimate destiny. - An-thony Robbins

We are successful because we use the right levelof abstraction. - Avi Wigderson

We can influence the future but not see it. -Stewart Brand

The mind will not focus until it has clear objec-tives. But the purpose of goals is to focus your at-tention and give you direction, not to identify a finaldestination. - John C. Maxwell

Of all the factors that contribute to adapting tochange, the single most important factor is the degreeto which individuals demonstrate resilience - the ca-pacity to absorb high levels of change and maintaintheir levels of performance. - Mark Kelly and LindaHoopes

Every piece of business strategy acquires its truesignificance only against the background of that pro-cess and within the situation created by it. It mustbe seen in its role in the perennial gale of creativedestruction; it cannot be understood irrespective of itor, in fact, on the hypothesis that there is a perenniallull. - Joseph Schumpeter

It is not the strongest of the species that survive,not the most intelligent, but the one most responsiveto change. - Charles Darwin

Resilience or some variation of this idea is aconcept that is explicitly if not tacitly implicit in al-most all explanatory models of behavior ranging fromthe biological to the social. It may be an inextricablepart of the ways in which we define and explain notonly human behavior but virtually all phenomena withvariable outcomes. - Meyer Glantz and Zili Sloboda

any approach able to deal with the changing com-plexity of real life will have to be flexible... It needsto be flexible enough to cope with the fact that ev-ery situation involving human beings is unique. Thehuman world is one in which nothing ever happenstwice, not in exactly the same way. This means thatan approach to problematical human situations hasto be a methodology rather than a method, or tech-nique... [Soft Systems Methodology] provides a set ofprinciples which can be both adopted and adapted foruse in any real situation in which people are intenton taking action to improve it. - Peter Checklandand John Poulter

I think that resilience is manifest competence de-spite exposure to significant stressors. It seems to methat you can’t talk about resilience in the absence ofstress. The point I would make about stress is the crit-ical significance of cumulative stressors. I think thisis the most important element. - Norman Garmezy

No plan survives contact with the enemy. - FieldMarshal Helmuth von Moltke

In many ways, coping is like breathing, an auto-matic process requiring no apparent effort... Is cop-ing always a conscious process? ...we so often mayrepeatedly respond to a recurring stressor that we loseour awareness of doing so. - Charles Richard Snyder

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What business strategy is all about; what dis-tinguishes it from all other kinds of business plan-ning - is, in a word, competitive advantage. Withoutcompetitors there would be no need for strategy, forthe sole purpose of strategic planning is to enable thecompany to gain, as effectively as possible, a sustain-able edge over its competitors - Keniche Ohnae

Rykiel (1996) defines model credibility as ”a suf-ficient degree of belief in the validity of a model tojustify its use for research and decision-making.”...there is no use talking about some overall universalmodel validity; the model is valid only with respect tothe goals that it is pursuing - Alexey Voinov

A principal deficiency in our mental models isour tendency to think of cause and effect as localand immediate. But in dynamically complex systems,cause and effect are distant in time and space. Mostof the unintended effects of decisions leading to pol-icy resistance involve feedbacks with long delays, farremoved from the point of decision or the problemsymptom. - John Sterman

everything in nature, everything in the universe,is composed of networks of two elements, or two partsin functional relationship to each other... The mostfundamental phenomenon in the universe is relation-ship. - Jonas Salk, Anatomy of Reality

What is the core of the matter? Why should amachine not be an excellent chess player? Is the taskinsoluble in principle? ... No. The problem seems tobe soluble... The machine may play chess badly, likea beginning amateur, but the machine is not guilty.Man is guilty. He has not yet succeeded in teach-ing the machine, in transferring his experience to it.What is involved in teaching a machine to play chess?- Mikhail Botvinnik

once you become aware of what means the mostto you, you’re less likely to put off something that’sreally valuable for something that matters much less...it’s knowing the difference between what’s importantand what isn’t that allows us to solve problems effec-tively. - Joy Browne

Intelligence is the ability to acquire knowledge,and not the knowledge itself. - George F. Luger

Where sustainability is not even a goal, it is un-likely that sustainability will be achieved by accident.And even if it is a declared goal, sustainability can-not be achieved where money, time, resources, and thecreative energies of individuals are wasted. - HartmutBossel

While a self-organizing system’s openness to newforms and new environments might seem to make ittoo fluid, spineless, and hard to define, this is not thecase. Though flexible, a self-organizing structure isno mere passive reactor to external fluctuations. Asit matures and stabilizes, it becomes more efficient inthe use of its resources and better able to exist withinits environment. It establishes a basic structure thatsupports the development of the system. This struc-ture then facilitates an insulation from the environ-ment that protects the system from constant, reactivechanges. - Margaret Wheatley, Leadership and theNew Science

If system behavior is guided by balanced referenceto basic orientors it will have the best chance for suc-cess in the long run... Systems which have evolvedunder evolutionary forces to be sustainable... can beviewed as having been designed in a way to achievebalanced satisfaction of basic orientors... To be ef-ficient and effective, path analysis, policy synthesis,and system design for sustainable development haveto take the orientor satisfaction of affected systemsinto account. - Hartmut Bossel

It should be obvious that in your workplace thereare some things you can control and some things thatyou can’t. The trick is being able to identify thosethings you can control and then to get busy control-ling them... My goal is to make you see that you havemore control over things than you think you do... Youcan regain a sense of control if you start to focus onissues where you can make a difference and stop wast-ing time on those where you can’t. - Karl Schoemer

Those who have to make the decisions should alsobe those who create the scenarios... We also recog-nize... that issues of power and influence are centralin determining how situations will unfold... power isa key determinant of... organizational... thinking...

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The key aim in writing scenarios is to grab the at-tention of the intended audience in order to conveyclear, concise and plausible stories about what typesof futures might unfold as a direct outcome of deci-sions made in the present and over time in relation tothe focal issue. - George Wright and George Cairns

Annotated bibliography:

http://mysite.verizon.net/vzesz4a6/current/id1268.html

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