Cognitive ModelingCognitive Modeling&&

Information Processing Information Processing MetaphorMetaphor

Cognitive Processes Cognitive Processes

Learning and MemoryLearning and MemoryThinking and Reasoning (Planning, Decision Thinking and Reasoning (Planning, Decision Making, Problem Solving ...)Making, Problem Solving ...)Analogy and metaphorAnalogy and metaphorLanguageLanguageVision-PerceptionVision-PerceptionSocial CognitionSocial CognitionEmotionsEmotionsDreaming and Consciousness Dreaming and Consciousness

The The IInformation-nformation-PProcessing rocessing MMetaphoretaphor

Mind has mental representations analogous to computer Mind has mental representations analogous to computer data structures, and computational procedures similar to data structures, and computational procedures similar to computational algorithms. computational algorithms. Symbolic View: mind contains such mental Symbolic View: mind contains such mental representations as logical propositions, rules, concepts, representations as logical propositions, rules, concepts, images, and analogies, and that it uses mental images, and analogies, and that it uses mental procedures such as deduction, search, matching, procedures such as deduction, search, matching, rotating, and retrieval. rotating, and retrieval. Connectionist View: mental representations use neurons Connectionist View: mental representations use neurons and their connections as mechanisms for data and their connections as mechanisms for data structures, and neuron firing and spreading activation as structures, and neuron firing and spreading activation as the algorithms – i.e., cognition can be explained by using the algorithms – i.e., cognition can be explained by using artificial neural networks artificial neural networks

Cognitive ModelingCognitive ModelingA model is a simplified (usually formal) A model is a simplified (usually formal) representation of realityrepresentation of realityCognitive modelingCognitive modeling Create formal (e.g. mathematical, algorithmic, Create formal (e.g. mathematical, algorithmic,

symbolic) representations of cognitive processessymbolic) representations of cognitive processes Then, use these models to predict or explain behavior Then, use these models to predict or explain behavior

associated with those cognitive processesassociated with those cognitive processes Computational modeling: the models usually Computational modeling: the models usually

implemented as computer programs with output implemented as computer programs with output corresponding to the predicted behaviorcorresponding to the predicted behavior

Example of cognitive process: categorizing objects Example of cognitive process: categorizing objects into groups. Modeling: use decision trees, or neural into groups. Modeling: use decision trees, or neural networks, or rules, etc.networks, or rules, etc.

The Function of Computational The Function of Computational Models Models

Computational Cognitive Model

Generates

Behaviour

Explains

Theory

Cognitive Process

Simulates

Describes

Implements

StrategiesStrategiesDevelop a model of some task or behaviour in Develop a model of some task or behaviour in order to learn more about it.order to learn more about it.Implement a pre-existing, verbally specified Implement a pre-existing, verbally specified highly complex theory to see if its theoretical highly complex theory to see if its theoretical assumptions are sufficient/necessary to account assumptions are sufficient/necessary to account for the target behaviour.for the target behaviour.Generate predictions/hypotheses to be then Generate predictions/hypotheses to be then tested by behavioural experiments.tested by behavioural experiments.Cognitive models of individual processes vs Cognitive models of individual processes vs “unified” approach – cognitive architectures“unified” approach – cognitive architectures

Practical Uses of Cognitive ModelingPractical Uses of Cognitive ModelingClinical psychology:Clinical psychology:

use cognitive models to assess differences in cognitive processing use cognitive models to assess differences in cognitive processing between normal individuals and clinical patients (e.g., schizophrenics). between normal individuals and clinical patients (e.g., schizophrenics).

Cognitive neuroscienceCognitive neuroscience use cognitive models to understand the psychological function of use cognitive models to understand the psychological function of

different brain regions. different brain regions.

Human factorsHuman factors use cognitive models to improve human-computer interactions and use cognitive models to improve human-computer interactions and

user interfacesuser interfacesArtificial intelligence and roboticsArtificial intelligence and robotics

use cognitive models for use cognitive models for automated detection of dangerous targetsautomated detection of dangerous targetsautomated recognition of speech or handwriting, or facesautomated recognition of speech or handwriting, or facesapproach and avoidance movement behavior of robotsapproach and avoidance movement behavior of robots. .

Economics and sociologyEconomics and sociology use cognitive models to construct computerized agents in agent based use cognitive models to construct computerized agents in agent based

models of market behavior or social network working.models of market behavior or social network working.

Cognitive ArchitecturesCognitive Architectures

Cognitive architecturesCognitive architectures are blueprints for are blueprints for intelligent agents. intelligent agents.

Unified frameworks for cognitive modeling Unified frameworks for cognitive modeling which attempt to model all cognitive which attempt to model all cognitive processes as well as the structural processes as well as the structural properties of the modeled systemproperties of the modeled system

Famous Famous Cognitive ArchitecturesCognitive Architectures

ACT-R, developed at , developed at Carnegie Mellon University under under John R. Anderson. .

Soar, developed under , developed under Allen Newell and John Laird at and John Laird at Carnegie Mellon University and the and the University of Michigan. .

EPIC, developed under David E. Kieras and David E. , developed under David E. Kieras and David E. Meyer at the Meyer at the University of Michigan

Apex developed under Michael Freed at NASA Ames Apex developed under Michael Freed at NASA Ames Research Center. Research Center.

Psi developed under Dietrich Dörner at the Otto-Psi developed under Dietrich Dörner at the Otto-Friedrich University in Bamberg, Germany. Friedrich University in Bamberg, Germany.

Marr’s Tri-Level Hypothesis RevisitedMarr’s Tri-Level Hypothesis Revisited

Three kinds of questionsThree kinds of questionsAll cognitive scientists agree that cognition All cognitive scientists agree that cognition involves information processing involves information processing To explain an information processor, three To explain an information processor, three different vocabularies have to be used – each different vocabularies have to be used – each requiring knowledge from different requiring knowledge from different disciplines disciplines "Trying to understand vision by studying "Trying to understand vision by studying only neurons is like trying to understand bird only neurons is like trying to understand bird flight by studying only feathers: it just flight by studying only feathers: it just cannot be done."cannot be done."

[ -- Continuing Marr (1982)]: “This duality – the representation and the processing of information – lies at the heart of most information-processing tasks and will profoundly shape Our investigation of the particular problems posed by vision.”

- If one accepts the information-processing approach, how does one move forward in understanding a complex information-processing system (e.g. some aspect of cognition, such as vision)?

~ Marr’s suggestion – Three Levels of Understanding

Levels of Analysis: Background

Three Levels (from Marr, 1982):

Levels of analysis (Levels of analysis (MarrMarr):):Three kinds of questions must be answeredThree kinds of questions must be answered

computationcomputation what is the problem?what is the problem?

inputs, outputsinputs, outputswhat is being computed or maximized?what is being computed or maximized?

algorithmalgorithm what are the methods?what are the methods?

Data representation, “process”Data representation, “process”

implementationimplementation what are the physical mechanisms?what are the physical mechanisms?

springs or neuronssprings or neurons

An Example: CalculatorAn Example: Calculator

Imagine a calculator that is beingImagine a calculator that is beingused to do some basic arithmetic.used to do some basic arithmetic.How would you explain to someoneHow would you explain to someonehow the calculator works?how the calculator works?

Implementation LevelImplementation LevelOne approach would beOne approach would beto explain the physicalto explain the physicaloperations of theoperations of thecalculator, by appealingcalculator, by appealingto the properties of itsto the properties of itstransistors, resistors,transistors, resistors,capacitors, and so on.capacitors, and so on.

What would thisWhat would thisexplanation miss?explanation miss?

Algorithmic LevelAlgorithmic Level

Another approachAnother approach would be to explainwould be to explain the informationthe information processing steps (theprocessing steps (the program) carried outprogram) carried out by the calculatorby the calculator

What would thisWhat would thisexplanation miss?explanation miss?

Computational LevelComputational LevelYet another approachYet another approachwould be to specify thewould be to specify thelaws of arithmetic, andlaws of arithmetic, andprove that the behaviorprove that the behaviorof the calculatorof the calculatorconforms to theseconforms to theseabstract lawsabstract laws

What would thisWhat would thisexplanation miss?explanation miss?

A + B = B + AA + 0 = AA+(B+C) = (A+B)+CA x B = B x AA x 0 = 0A x 1 = AA x(B+C) = (AxB)+(AxC)….

The Tri-Level HypothesisThe Tri-Level Hypothesis

Symbolic View of the Algorithm and Symbolic View of the Algorithm and Representation LevelRepresentation Level

An informationAn information processor uses processor uses symbolssymbols to represent the worldto represent the world

Rules are used toRules are used to manipulate thesemanipulate these symbols or tokenssymbols or tokens

When rules are applied,When rules are applied, the symbolthe symbol manipulations preservemanipulations preserve meaningmeaning

One solves problems, orOne solves problems, or finds new finds new meanings, bymeanings, by manipulating manipulating symbolssymbols according to the “rulesaccording to the “rulesof the game”of the game”

Types of RepresentationsTypes of Representations

Formal Logic:Formal Logic: assumes mental representations similar to sentences assumes mental representations similar to sentences

in predicate logic. in predicate logic. deductive and inductive procedures, applied to the deductive and inductive procedures, applied to the

sentences, produce the inferences. sentences, produce the inferences.

Rules (IF … THEN ):Rules (IF … THEN ): many cognitive processes such as planning can be many cognitive processes such as planning can be

modeled by rule-based systems modeled by rule-based systems assumes mental representations as rules and assumes mental representations as rules and

procedures for using these rules to search a space of procedures for using these rules to search a space of possible solutions, and procedures for generating new possible solutions, and procedures for generating new rules. rules.

Types of RepresentationsTypes of Representations

Concepts:Concepts: mental representations are concepts (related to words) and mental representations are concepts (related to words) and

relationships among the conceptsrelationships among the concepts often represented as a set of featuresoften represented as a set of features mental procedures including spreading activation, matching, and mental procedures including spreading activation, matching, and

inheritance used to produce behaviorinheritance used to produce behavior

Analogies:Analogies: computational models simulate how people retrieve and map computational models simulate how people retrieve and map

source analogs in order to apply them to target situations. source analogs in order to apply them to target situations. assumes people have verbal and visual representations of assumes people have verbal and visual representations of

situations that can be used as cases or analogs, as well as situations that can be used as cases or analogs, as well as processes of retrieval, mapping, and adaptation that operate on processes of retrieval, mapping, and adaptation that operate on those analogs. those analogs.

the analogical processes, applied to the representations of the analogical processes, applied to the representations of analogs, produce the behavior. analogs, produce the behavior.

Types of RepresentationsTypes of Representations

Images:Images: pictorial representations capture visual and spatial information in pictorial representations capture visual and spatial information in

a much more usable form than lengthy verbal descriptions. a much more usable form than lengthy verbal descriptions. so, people have visual images of situations, and processes such so, people have visual images of situations, and processes such

as scanning and rotation that operate on those images. as scanning and rotation that operate on those images. the processes for constructing and manipulating images produce the processes for constructing and manipulating images produce

the intelligent behavior the intelligent behavior some metaphorical aspects of language may have their roots in some metaphorical aspects of language may have their roots in

imagery.imagery.

Connectionist Networks (neural nets):Connectionist Networks (neural nets): people have representations that involve simple processing units people have representations that involve simple processing units

linked to each other by excitatory and inhibitory connections. linked to each other by excitatory and inhibitory connections. processes that spread activation between the units via their processes that spread activation between the units via their

connections, as well as processes for modifying the connections connections, as well as processes for modifying the connections and learning. and learning.

ExerciseExerciseConsider the addition example given earlierConsider the addition example given earlier

Write a more general algorithm for adding Write a more general algorithm for adding any two 2-digit numbers (you can use any two 2-digit numbers (you can use symbols to represent digits and IF-Then symbols to represent digits and IF-Then rules to model conditions.rules to model conditions.

Exercise 2Exercise 2

Can you solve the following problem?Can you solve the following problem?

Exercise 2 (cont.)Exercise 2 (cont.)How do you solve the previous problem How do you solve the previous problem after reading the following story?after reading the following story?