Metacognition in Computation: A selected history

Michael T. CoxBBNT Cambridge

22 March 2005 2

Why Metacognition?

“What then can be the purport of the injunction, know thyself? I suppose it is that the mind should reflect upon itself.”

-- Augustine, De Trinitate, 16th century

22 March 2005 3

Why Metacognition?

• Separates us from the rest of the species

• Separates smarter people from less smart

• Provides a heuristic basis for decisions– E.g., I am good at home repair, so I can risk

embarrassment by volunteering to fix the broken pipe rather than calling a plumber.

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Metacognition is Ubiquitous

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Why NOT Metacognition?

• Complexity – space and time

• Actual human limitations– Easier to show when metacognition does not

work rather than how it does

• AI hype

22 March 2005 6

AI Hype

“Once self-description is a reality, the next logical step is self-modification. Small, self-modifying, automatic programming systems have existed for a decade; some large programs that modify themselves in very small ways also exist; and the first large fully self-describing and self-modifying programs are being built just now. The capability of machines have finally exceeded human cognitive capabilities in this dimension; it is now worth supplying and using meta-knowledge in large expert systems.”

-- Lenat, Davis, Doyle, Genesereth, Goldstein, and Schrobe 1983 (p. 238)

22 March 2005 7

What is Metacognition?

• Meta-X is defined as “X about X”• Metacognition is cognition about

cognition• Metareasoning is reasoning about

reasoning• Metaknowledge is knowledge about

knowledge• Metamemory, metarepresentation,

metacomprehension, metalogic, metaplans,meta...

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But what about…

• Meta-levels

• Reflection

• Introspection

• Self-awareness

• Self-explanation

• Consciousness?

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Outline of Presentation

• Psychology, Metacognition, and Human Behavior

– Cognition and Metacognition

– Problem Solving and Metacognition

– Metamemory

• Artificial Intelligence, Metareasoning, and Introspection

– Logic and Belief Introspection

– Knowledge-Based Systems, Metareasoning, and Control

– Model-Based Reasoning, Case-Based Reasoning and Introspective Learning

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What is Not Being Covered?

• Social Psychology

• Philosophy

• Cognitive Neuroscience

• Consciousness Studies

• Theological Accounts

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Psychology, Metacognition, & Human Behavior

• Earliest Research – circa 1900– Brown, A. 1987. Metacognition, Executive Control, Self-

regulation, and Other More Mysterious Mechanisms. In F. E. Weinert and R. H. Kluwe eds. Metacognition, Motivation, and Understanding 65-116. Hillsdale, NJ: LEA.

• Text comprehension and metacognitive activities studied, but under different names.

• Not to be confused with introspectionism

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Cognition & Metacognition

• Earliest Research – John Flavell– Flavell, J. H. 1971. First Discussant’s Comments: What Is

Memory Development the Development of? Human Development 14: 272-278.

– Flavell, J. H. 1976. Metacognitive Aspects of Problem Solving. In Resnick ed. The Nature of Intelligence, 231-235. Hillsdale, NJ: LEA.

• Much of the work has been in the child development and cognitive aging research communities

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Wellman’s Theory

• Wellman, H. M. 1992. The Child's Theory of Mind. Cambridge, MA: MIT Press.

• Children come to construct a naive theory of mind by observing the difference between self and others– Before age of three – no distinctions – At age of three – difference between wants and

actions; between ideas and reality– After age of three – mind as processor and interpreter

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Metacognitive Variables

• Person Variables– Deals with the individual and others– Cognitive psychologists can recall many facts about

cognition

• Task Variables– Concerns the type of mental activity– Harder to remember nonsense words

• Strategy Variables– Alternatives to mental tasks– To remember a list it helps to rehearse

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Theory-Theories

• Theories have – Coherence– Ontology– Causal-explanatory structure

• Theories of Mind– Mental constructs self-refer– Distinctions between things and ideas– Desires and beliefs effect thought and action

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Children’s Theory of Mind

• Different than adults

• More than just a collection of facts about mental phenomena

• Experiment for 3-yr-olds– Sally sees candy put in a bag– Sally leaves room– Candy placed in a drawer– Sally returns, where will she look for candy?

22 March 2005 17

Problem Solving & Metacognition

• Earliest Research – Dörner– Dörner, D. 1979. Self-Reflection and Problem-solving. In F. Klix

ed. Human and Artificial Intelligence, 101-107. Amsterdam: North Holland.

• Subjects that introspect versus those that do not with all else the same

• Surprisingly very little work altogether

22 March 2005 18

Derry’s Theory

• Comprehensive model of reflective problem-solving for mathematical word problems

• Inspired by ACT* (Anderson)• Four basic phases

1. Clarifying a problem2. Developing a strategy3. Executing a strategy4. Monitoring/Checking

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Derry’s Experiment

• Computer-based instructional system

• Teaches math word problems to military personnel and college students

• Assumption: Goal backchaining and MEA form bases for human problem-solving

• Gather subject protocols during testing

• Categorize protocols and correlate with performance

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Derry’s Results

• Neither group had linear performance• Protocols fell into clarification and execution• Considered checking math answers as

metacognitive

Group Clarify Plan Execute Check Other

Army (n=8)

44 7 36 3 10

College (n=8)

41 2 49 3 5

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Swanson’s Research

• Separate cognitive abilities from metacognitive abilities

• Standardized test scores and meta-cognition questionnaires (Hultch, Hertzog, Dixon, & Davidson 1988)

• Measure problem-solving performance

• High/Low aptitude interacts with high/low metacognition

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Metamemory

• Earliest Research – John Flavell– Flavell, J. H., and Wellman, H. M. 1977. Metamemory. In R. V.

Kail, Jr., and J. W. Hagen eds. Perspectives on the Development of Memory and Cognition, 3-33. Hillsdale, NJ: LEA.

• Knowledge of and memory for memory

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Knowing without Remembering

22 March 2005 24

Kausler and Lovelace’s Theory

Kausler– Off-line memory evaluation– On-line memory evaluation

Lovelace• Pre-performance estimates (predictions)• On-line memory monitoring

– FOKs – Postdictions– Reality monitoring– JOLs

– Memory performance monitoring

22 March 2005 25

Information Processing Models

• T. Nelson and Narens – Information processing view– Monitoring component and control component

• M. T. H. Chi and K. VanLehn – The self-explanation effect

• P. Pirolli and M. Recker– Soar model + GRAPES– Subjects that explained between experiments

tended to learn better

22 March 2005 26

Reder’s Theory

• Game show paradigm• Two stages of memory

retrieval exist– Fast familiarity judgment– Slower search stage

• Conclusion– Correlated with question

terms not answers

22 March 2005 27

SAC Model

• Source of Activation Confusion

• Spreading activation model

• Base-line strength change as the power function

• Activation change due to neighbors is

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22 March 2005 28

AI, Metareasoning & Introspection

• Earliest Research – Minsky and McCarthy– Minsky, M. L. 1965. Matter, Mind, and Models. In Proceedings of

the International Federation of Information Processing Congress 1965 (Vol. 1) 45-49.

– McCarthy, J. 1959. Programs with Common Sense. In Symposium Proceedings on Mechanisation of Thought Processes (Vol. 1), 77-84. London: Her Majesty’s Stationary Office.

• Models of Models

• Declarative Knowledge for the Self

22 March 2005 29

Minsky’s Theory

• Minsky, M. L. 1965. Matter, Mind, and Models. In Proceedings of the International Federation of Information Processing Congress 1965 (Vol. 1) 45-49.

• To answer questions about the world and the self in the world, an agent must have a model it can query

• W, M, W*, M*, W**, M**

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McCarthy’s Theory

• McCarthy, J. 1959. Programs with Common Sense. In Symposium Proceedings on Mechanisation of Thought Processes (Vol. 1), 77-84. London: Her Majesty’s Stationary Office.

• Knowledge as logic

• Logic as thinking

• What does it mean for a robot to be conscious?

22 March 2005 32

Logic & Belief Introspection

• Self-Reference and “aboutness” (Perlis)– Liar’s Paradox from time of Socrates– This sentence is false.

• FOL axiomization and possible worlds (Moore)

• Belief is different than facts (Hintakka)

• Model-Theoretic reasoning

• Metalogics and proving provability

22 March 2005 33

Konolige’s Deduction Model

• Alternative to Possible Worlds Semantics

• Deduction Structure is a mathematical abstraction of bounded belief systems

• Machines and introspective machines

• Intrinsic and extrinsic self-beliefs

• Separation of IM from M resolves some problems of self-reference

22 March 2005 34

Logical Representations

• Is-Complex-wrt

(John,

)

• How to handle?

))"(,()(." pAboutpKnowspPersonp

22 March 2005 35

Knowledge-Based Systems, Metareasoning & Control

• Earliest Research – Metaknowledge in expert systems– Barr, A. 1977. Meta-Knowledge and Memory, Technical Report,

HPP-77-37. Stanford University, Department of Computer Science, Stanford, CA.

– Davis, R. 1976. Applications of Meta-Level Knowledge to the Construction, Maintenance, and Use of Large Knowledge Bases. Stanford HPP Memo 76-7. Stanford University.

• Metarules: the red herring of AI

22 March 2005 36

Davis’ Theory

• Knowledge engineering in MYCIN

• Metaknowledge 1. Schemas2. Function templates3. Metarules4. Rule models

• Rule models help interpret what expert asserts

Performance ProgramDomain

Expert

TEIRESIAS

knowledge transfer

explanation Inference Engine

Knowledge Base

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Example Rule Model

INVESTMENT-AREA-IS1. Examples ((rule116 0.3) (rule050 0.7)

(rule037 0.8) (rule095 0.9) (rule152 1.0))2. Description

– Premise ((returnrate same notsame 3.8) (timescale same notsame 3.8) (trend same) ((returnrate same)(timescale same) 3.8) …

– Action ((investment-area conclude 4.7) (risk conclude 4.8))…

3. More-general (investment-area)4. More-specific (investment-area-is-utilities)

22 March 2005 38

Model-based Understanding & Learning by Experience

Knowledge Base

Rule Models

Rule Acquisition(knowledge acquisition)

Expert

(dialog)

(model-directed understanding)

(concept formation)

22 March 2005 39

Problems with Expert Systems

• Confuses abstraction with metacognition

• Confuses control with metacognition

• Self-understanding software tangent?

• Explanation is not a rule chain or proof tree

• Knows what it does not know?

22 March 2005 40

Metareasoning

• Earliest Research – Bounded rationality– Simon, H. A. 1955. A Behavioral Model of Rational Choice.

Quarterly Journal of Economics 69: 99-118.

• Earliest Research – Good’s Type II rationality– Good, I. J. 1971. Twenty-Seven Principles of Rationality. In V. P.

Godambe and D. A. Sprott eds. Foundations of Statistical Inference. Toronto: Hold, Rinehart, Winston.

22 March 2005 41

Wesfald’s Theory

• Treating computation selection as action selection by maximizing expected utility– Cost of time (world changes by itself)– Benefit of better action choices

– Execution cost– Resource cost

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System Unification

Unifies decision-making systems

• Decision-theoretic systems

• Production systems• Goal-based systems• Reactive systems• EBL systems

Unifies meta-cognitive systems

• MRS (Genesereth)• TEIRESIAS (Davis)• Soar (Newell)

22 March 2005 43

Decision Stages and Shortcuts

Condition (s)

Condition (result(a,s))

Utility (result(a,s), v)

Best (a,s)

A

B

EF

C

DTD

22 March 2005 44

Model-based Reasoning & CBR

• Earliest Research – Schank’s emphasis on memory and representation– Schank, R. C., Goldman, N., Rieger, C., and Riesbeck, C. K.

1972. Primitive Concepts Underlying Verbs of Thought (Stanford Artificial Intelligence Project Memo No. 162. Stanford, CA: Stanford University, Computer Science Department. (NTIS No. AD744634)

• Using Conceptual Dependency primitives to represent remember, forget, think, expect…

22 March 2005 45

Case-Based Explanation

• Provides a framework for interpreting Failures– In world actions– In reasoning actions (e.g., memory retrieval)– In social actions

• Example: Dog barking story– S1 Police & Dog enter airport baggage area– S2 Dog sniffs luggage.– S3 Dog Barks at luggage.– S4 Police arrests suspect.

22 March 2005 46

Computational Introspection

• To reason about the self…

• When reasoning about the world fails use meta-reasoning to explain the failure

• Map from symptom of the failureto the cause of the failure

• Learn

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Symptoms of Failure

Actual eventdoes not exist

FalseExpectation

Impasse

Surprise

Contradiction

Unexpected Success

Actual event exists

Expectation does not exist

Expectationexists

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Causes of Failure

Missing

Incorrect

Correct

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Stranded Motorist Example• Planning a vacation

– Destination– Reservation– Supplies– Gas

• Plan Execution– Goes to store– Buys supplies– Drives to mountains– Runs out of gas

• Failure Recovery– Get gas can– Walk to gas station or hitch-hike– Fill can with gas– Return to Fill tank– Continue

• Failure Repair– Regress goals to features in initial state– Use features as index to store as new case

• Alternate Repair– Reason about the reasoning that led to the failure– Cause was forgetting to fill car with gas at store– Form association between going on long trip and

checking gas gauge

Causal Possibilities Tree

• Sub-goals– Be at store– Make purchases

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Forgetting to Fill-Up with Gas

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Problems with Metacognition

• Control and rules– Abstract rules are not really different from

concrete rules

• Metaknowledge– Knowledge about facts is not really different

from ordinary facts

• Many synonymous and overloaded terms

• Overstating Benefits

22 March 2005 52

Conclusion

• The “Many-headed Monster of obscure parentage” –Brown (1987)

• Lessons to be learned

• Failures to be avoided

• Current research has the potential to be qualitatively different because of the technical maturities and funding commitments

22 March 2005 53

A Grain of Salt

“To know oneself is only half as good as knowing two selves.”

--Homer

(Simpson)