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SOCIAL SYSTEMS MODELING USING INTELLIGENT MULTI-AGENT SYSTEMS
Joaquim Filipe([email protected])
School of TechnologyPolytechnic Institute of SetúbalPortugal
This work has been supported in part by the Croatian Science Foundation under the project no. 8537.
Joaquim Filipe (c) 2014 MMORPG Project 2
Information Systems modeling Organizational Semiotics Norms and Social Psychology Information Fields
Agent Paradigms Individual vs. Social focus EDA vs. BDI Agent Models Agency Theory Multi-Agent Systems
Conclusions
Overview
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This presentation intends to introduce a theoretical framework that integrates several theories/well known areas of knowledge: Organizational Semiotics Social Psychology Agency Theory
No MMORG tools or software will be referred in this presentation
Metatheoretical Focus
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MMORPGs facilitate communication between players and involve some degree of teamwork for parts of the game.
Sometimes there is a hierarchical structure (organization).
Need to represent knowledge about The player herself/himself/itself The other players Available roles Communication / Action rules Social norms
MMORPGs are Social Systems
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Social Systems ARE Information Systems
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INFORMAL Inf.System: a sub-culture where meanings are established, intentions are understood, beliefs are formed and commitments with responsibilities are made, altered and discharged
FORMAL Inf.System: bureaucracy where form and rule replace meaning and intention
IT System: Mechanisms to automate part of the formal system
Three main layers of the real information system (Stamper 1996)
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The science of signs
Information is made of signs (the atoms of information)
‘A sign … is something which stands to somebody for something in some respect or capacity.’
(Peirce, 1931-58)
Information and Semiotics
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Information is a complex concept. Social issues are relevant: information is constructed by people (constructivism).
Semiotics studies all aspects related to the creation, use and termination of signs. Different aspects of signs must be studied as social
constructs: the (interpreted/negotiated) meaning of signs (semantics),
the way they are used (pragmatics) and how they affect social power systems (social world)
Information Systems Information is carried by signs and used for semantic, pragmatic
and social purposes.
Semiotics, Information and Social Systems
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Semiotics LadderSOCIAL WORLD - Commitments,
Human Information contracts, law, culture, ...
Functions PRAGMATICS - intentions, communication,
conversations, negotiations, …
SEMANTICS - meanings, propositions,
validity, truth, signification, denotations,…
The IT SYNTACTICS - formal structure, language, logic,
Platform Data, records, deduction, software, files, …
EMPIRICS - pattern, variety, noise, entropy,
channel capacity, redundancy, efficiency, codes, …
PHYSICAL WORLD - signals, traces, physical distinctions,
hardware, component density, speed, economics, …
The Semiotics ladder (Stamper, 1973)
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Norms are deontic entities (obligations/responsibilities) Wright (1963) defines ‘Norm’ as partial synonyms which includes, ‘pattern’,
‘standard’ and ‘type’. So are ‘regulation’, ‘rule’, and ‘law’. Deontic Logic is a higher-order modal logic based on the Obligation operator.
Norms are determined by society or collective agents, and serve as a standard for the members to coordinate their actions.
These social constructs may represent: Common (shared) knowledge Patterns of behaviour which are acceptable within the social
context. Power relations and other social structures
Group members are responsible for adopting and using these norms.
The prime social entity: Norm
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Norms can be:
Perceptual
Cognitive
Behavioral
Evaluative
Social Psychology Classification of Norms
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Corresponding intentional attitudes:
Ontological: to acknowledge the existence of something
Epistemic: to know or adopt a degree of belief
Deontic: to be disposed to act in some way
Axiological: to be disposed in favor or against something in value terms
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Sets of norms adopted and used by all the group members. An agent who comes into the group is influenced by
the group’s norms and either adopts them or becomes an “outsider”.
Coallition formation requires merging different information fields (a common problem in emergent organizational structures e.g. VOs)
An organization may need to split up due to information field clashes (e.g. Departments in Universities)
Information Fields
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Several interests may be at stake simultaneously.
Example:
Interest Alignment
- Ind.2 may have interest in situation A while Ind.1 may be interested in situation B If A B it’s ok, otherwise there is a clash of interests
- Ind.2 may be subject to contradictory norms
Social Group 1
Ind.1Ind.2
Social Group 2
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Social Systems and Information Fields
Information Field: System of norms accepted by a community
Semantics, Pragmatics, Social
Shared ontology: Information Fields may overlap
Information Fields can be populated by Individual agents, Collective agents (=>nested IFs), Abstract agents (roles – reflecting organizational
norms).
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<Abstract Agent>::= <set of commitments> Normative (shared) commitments can be
about any type of norms: Perceptual, Cognitive, Behavioral or Evaluative.
Commitments involve Obligations and Authorisations
Roles are Social “Contracts”
A commitment is: <Commitment>::= O | P | F :<agent>:
<norm(args)>
Roles as Abstract Agents
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Useful for social modeling because: Social Systems are (Distributed) Information
Systems Multiple agents and resources Systemic properties (boundaries, control, internal
components, input/output, etc.)
Each individual plays one or more roles but it Has a degree of autonomy Is situated in a social normative and communicative
environment Exhibits a goal-directed behavior Uses knowledge and different forms of reasoning
(inspired in Wooldridge and Jennings definition of agent)
Multi-Agent System Metaphor
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Internal Model: BDI (Beliefs, Desires and Intentions)
Beliefs = set of true propositions about the world
Desires = set of objectives (not necessarily coherent)
Intentions = set of plans
Agent is permanently in an observe-reason-act cycle and adjusts its internal model according to logical rules
Traditional Agent Models
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BDI primitives are meant mainly for creating mental models.
Social context is not critical for mental models.
Desires and Intentions belong to the same norm type (behavioral).
No primitives for perceptual or evaluative norm types.
No concern with the duality individual/social responsibility
Shortcomings of BDI
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The organizational semiotic stance ties every item of knowledge to an agent, who is, in a sense, responsible for it. Formally:
<wff commitment> ::= <agent-term> <norm-term (args)>
Instead of an objective truth, there is a concept of truth that corresponds to the set of agents’ beliefs. Agents are responsible for the consequences of the beliefs they choose to adopt (epistemic component) wff ::= BA(P)
Agents are responsible for their behaviour (deontic component) wff ::= OA(P)
Agents are responsible for their values (axiomatic component) wff ::= VA(P)
Formal Responsibility
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action perception
Axiological Component (values)
Epistemic Component (knowledge)
Deontic Component (behavior)
EDA ModelEpistemic-Deontic-Axiologic
is a pragmatic function that filters perceptions, according to the agent ontology, using perceptual and axiological norms, and updates one or more model components. is an axiological function, that is used mainly in two circumstances: to help decide which signs to perceive and to help decide which goals to put in the agenda and execute is a knowledge based component, where the agent stores his beliefs both explicitly and implicitly, in the form of potential deductions based on logical reasoning.
is a set of plans, either explicit or implicit, the agent is interested in and may choose to execute
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EDA Agent Model
Semiotics+Social Psychology+Agency Theory
How to Formalise?
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There are several agency logics, based on the work of several philosophers.
Belnap’s STIT (See to it that) Inspired in Austin (theory of speech acts) Belnap proposes a new
class of sentences: agentives Agentive wff: <agent-term> <complement(action)>
sees to it that Q
To refrain from acting is an action; not acting is not an action
[α stit: ¬Q] ≠ ¬[α stit: Q]
Agency Theory
[ : ]stit Q
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An action is always performed by an agente who is responsible for it.
In situations where an agent delegates an action to another agent, who is responsible for the action?
[α stit: [β stit: Q]] is meaningless because an agent is, by definition, autonomous.
All α can do, when it delegates on β, is to create an obligation:
[α stit: O[β stit: Q]]This is a Deontic Action-Logic statement.
Delegation and Responsibility
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( )B
Knowledge Representation Epistemic component (Beliefs)
Non-monotonic Logic; belief revision. Belief operator
Deontic component (Obligations) Deontic Agency Logic Agentive Obligation operator
Axiologic component (Values) Prioritised Default Logic (norms as default
rules) Preference defined by a partial order on
norms
[ : [ : ]] ( )stit O stit O
( , )E
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EDA Agents
This structure applies to
- Individual agents
- Collective agents
(a collective agent is an agent)
- Abstract agents (roles)
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Multi-Agent EDA Systems
action perception
Axiological Component (values)
Epistemic Component (knowledge)
Deontic Component (behavior)
action perception
Axiological Component (values)
Epistemic Component (knowledge)
Deontic Component (behavior)
action perception
Axiological Component (values)
Epistemic Component (knowledge)
Deontic Component (behavior)
Communicative Agents
Normative Agents
Social Agents
Goal-Directed Agents
Are Dynamic/Open Distributed Systems
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Social vs. Individual Goalsor why agents act:
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Is a model with sound theoretical support: The model is based in social psychology theory, philosophy and logic.
Unifies individual and social motivations under the concept of obligation This reduces the number of needed concepts, when compared
to other agent models such as BDI (which uses two “motivational” operators).
The same model structure (EDA) can be used for individual and collective agents, This enables a simple recursive structure for organizational
models, where individual models inherit norms from collective models.
Advantages of the EDA Model
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Not widespread Since it is based on higher order
modal logic it is difficult to compute, in general.
No software development tools
Disadvantages of the EDA Model
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Social Groups can be seen as multi-agent systems composed by individual agents in social settings. EDA agents can be individual or collective. A collective agent defines a (shared) information field. A role can be modeled as na abstract agente.
Organizational Semiotics, Social Psychology and Agency Theory provide the basis for a normative agent model. The EDA model provides an adequate formal support
(logic) for each model component: agent implementation can be based on a sound theory instead of ad-hoc mental models.
Conclusions
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“There’s nothing as practical as a good theory” (Ludwig Boltzman)
Thank you for your attention
This work has been supported in part by the Croatian Science Foundation under the project no. 8537
October 14