Theories of high level cognition in natural and artificial ... · cognition: circa 1970-1990...

Theories of high level cognition in natural and artificial systems: can we agree on any underlying principles?

John Fox

University of Oxford (Engineering Science)UCL (Oncology, Royal Free Hospital) www.cossac.org

Cognitive systems

“… are natural or artificial information processing systems, including those responsible for perception, learning, reasoning, decision-making, communication and action” (www.foresight.gov)

http://www.foresight.gov/

High level cognition: medical expertise

Imaging Staging Radiotherapy Prognosis

Biopsy Chemotherapy Hormone therapy Risk assessment

Diagnosis Surgery Adjuvant therapy Trial eligibility

Summary of talk

• What is cognition? depends on your objectives– “Scientific”, empirical– Axiomatic, “rational”– Engineering, practical

• Research programme on medical expertise – A general model for HLC?

• High level cognition and folk psychology– A meeting place for different tribes in

cognitive science?

Rational principles, Axiomatic theories

Empirical studies of natural cognition

Practical engineering, application design

Understanding high level cognition: circa 1970-1990

Memory, semantic networks, spreading

activation … heuristics & biases

Logic/deductionBayesian inference

Decision theory

Expert systems,Knowledge

representation tools,

Ontologies

Understanding high level human cognition: cognitive psychology




“Making decisions under the influence of memory” Psych Review, 1980

Run me

Issues

• Good account of the subject behaviour– Focused on group data – Individual differences left unexplained

• Task still very simple compared with real medical expertise– We want an account of the whole

process – Autonomous operation

Understanding high level cognition: engineering




A model of medical expertise

Clinical

objectives

Options

Selectoption

-

Patient data

Care plans

Actions

Safe and Sound: Artificial Intelligence in Hazardous ApplicationsFox, and Das, AAAI and MIT Press 2000

Decisions Plans

Modelling clinical processes

Medical case,

clinical requirements

Task and process

modelling

Specification and Verification Of model

Behaviour

testing

Clinical

deployment

Medical case,

clinical requirements

Task and process

Modelling

Specification and Verification Of model

Performance

testing

Clinical

deployment

The patient journeyGP referrals, MedInfo 2001

Detection of breast abnormalities,

Med Image Anal, 1999

Family history and risk assessment

BMJ 1999, 2000

Triple assessmentB J Cancer 2006

Personalised care planning and counselling

Cancer Education

Clinical decision support

ApplicationsSupport for cancer multidisciplinary decision-making(Patkar et al BASO 2008, San Antonio 2009, Barcelona 2010)

Spoken language dialogue interfaces for cognitive agents (Beveridge and Fox, J Biomed Informatics, 2006)

Triple assessment in breast cancer (Hurt, Patkar et al Brit J Cancer 2006)

Dose adjustment in prescribing for children with ALL (Bury and Hurt Brit J Haematology, 2005)

Counselling women at risk of breast/ovarian cancer

(Glasspool et al Methods of Information in Medicine 2004)

GP referrals for common cancers (Bury et al MEDINFO 2003)

Genotype of HIV+ patients interpretation and selection of anti-retrovirals (Tural et al AIDS 2002)

Genetic risk assessment (Coulson, Glasspool and Emery BMJ 1999, 2000)

Support for mammographic screening (Taylor et al, Medical Imaging 1999)

Prescribing in general practice (Walton et al, BMJ 1997)

Understanding high level cognition: “agents” 1990-2010



Practical engineeringDesign

Formalising the domino model

Goals

Options

Commitments-

Beliefs

Plans

Actions

Das, Fox et al J Exp. Theor. AI 1997, Fox, and Das, MIT Press 2000Fox et al IEEE Intelligent Systems, 2006

Run me

Runme 2

From autonomous agents to frontal lobe function

Shallice T “Fractionation of the Supervisory System” in Stuss and Knight (eds) Principles of Frontal Lobe Function, OUP 2002

Shallice T “Contrasting domains in the control of action: …” in Minataka & Johnson (eds) Attention and Performance, 2006

1. Articulation of a goal (abstracting from the current situation)

2. Production of one or more solutions to attain the goal3. Selection between them and the consequent decision to

act4. Articulation of the procedure into a sequence of

implementable steps5. The realisation of the steps as actions6. Checking actions are realising the goal(s)

A general schema for cognitive science?

• It is proving useful in a variety of ways– As a general agent model (wider than BDI)– As a productive engineering framework– As a rationale for understanding human “executive

function”

• Can it support interdisciplinary cognitive systems research? – It is not grounded in a rigorous experimental

programme – It is not clear what status the objects in the model

have, or how computational processes relate to neuro-cognitive mechanisms

– It adopts a kind of folk psychology perspective, with all the philosophical and other issues this implies

High level cognition and folk psychology

Functionalism (1)

• “A theory of mind which implicitly defines terms such as "believe", "want" and "desire” relating sensory experiences to mental states; mental states to other mental states; and mental states to behaviour”

• “A theory of human mind-brain which postulates a data structure or knowledge representation which mediates between our observations of behavior-in-circumstances and our predictions and explanations of that behaviour”

Functionalism (2)

• Functionalism is a theoretical level between the physical implementation and behavioural output (Marr, 1982)

• Led to the adoption of BDI (beliefs, desires, intentions) model of agency in AI.

High level cognition, expertise

ConcreteImplementations

Critique of folk psychology

• The words that represent “mental states” are at best imprecise and quite possibly meaningless– They are culturally defined– Not “real” states of brain-mind

• As a “theory” folk psychology is scientifically barren: it makes no testable predictions

General cognitive principles?



Practical engineeringDesign

Can we understand the core functions of

high level cognition in a generic or canonical

form?

Bayesian inferenceStatistics, decision theory

Countless applicationsCognitive science (Judgement,

perception, NL …)

DeductionPhilosophy, computer scienceCognitive science (psychology

of reasoning)

Neural networksAI, neuroscience,

robotics, applications

Spreading activationCognitive science

Goals

Possible worlds

Decisions

Situations

Plans

Actions

Principle 1: Belief

Any autonomous agent (natural or artificial) needs to maintain a consistent set of beliefs and expectations with respect to its current environment

Goals

Possible worlds

Decisions

Situations

Plans

Actions

If a belief or plan entails a threat or an opportunity then an autonomous agent must be able to coordinate its behaviour to mitigate the threat or exploit the opportunity

Motivation/DrivesClassical psychology

Utilities, preferencesEconomics,

Management …

Non-classical logicAI

computer sciencephilosophy

Other usesEducation

Organisational psychologySoftware engineering

Folk psychology

Principle 2: Goals

If an agent has a goal for which it can propose a possible way of achieving the goal then this should be viewed as a candidate solution for assessment against alternatives

Goals

Possible worlds

Decisions

Situations

Plans

Actions

General PSPsychology,

AI, robotics

Kinds of PSExplanation

Constraint solvingPlanning, Design …

Principle 3: Problem solving

Goals

Possible worlds

Decisions

Situations

Plans

Actions

Every independently justified line of reasoning for or against a candidate problem solution should be considered when assessing decision options

Hypothetical reasoningBayesian inference

Epistemic logic

Practical reasoningDecision theory

Deontic logic

Debate/disputeAI,

multi-agent systemsLaw …

RhetoricPragma-dialecticsCritical questions

Principle 4: Argumentation

Goals

Possible worlds

Decisions

Situations

Plans

Actions

The more independent lines of reasoning there are that are consistent with a decision option (belief or plan) the greater an agent’s preference for the

option

Principle 5: AggregationJudgement

Decision psychologySocial choice theory

Multi-criteria decision-making

Decision theoryEvidential reasoning

Expected utilityStatistical decision theory

Decision logics

Goals

Possible worlds

Decisions

Situations

Plans

Actions

If an agent determines that its current preferred option will not change with further information then it can safely commit to that option

AcceptanceLogic

Philosophy

and truthand beliefand action

and altruism …

Principle 6: Commitment

Goals

Possible worlds

Decisions

Situations

Plans

Actions

If an agent's commitments include actions or plans that are necessary to achieve one or more of its goals, then these should be enacted in a way that is optimised with respect to the agent’s priorities.

Computer scienceProgram execution

AI, roboticsPlan enactment

Cognitive neuroscienceContention scheduling

EngineeringBusiness process modelling

Workflow

Principle 7: Plan enactment

Principle 8: Action

If an agent has an intension/plan to carry out an action and there is no reason to postpone its execution then implement the appropriate act

Ballistic operationEngineering

Engineering psychology

Conditional operationSoftware

Servomechanismshardware

Actions

Goals

Possible worlds

Situations

Plans Decisions

An agent should continually check that its actions have all and only the anticipated and intended effects Goals

Possible worlds

Decisions

Situations

Plans

Actions

Principle 9: Monitoring

Signal processingVision science/psychophysics

Hearing and speechNeuroscience

Instrumentation …

PerceptionCognitive psychology

AI

ReflectionAI, philosophySelf monitoring

Consciousness studies

Cognitive principles; standard components? IEEE Intelligent Systems, 2006

Canonical principles?

Fox et al, IEEE Intelligent Systems, 2006

Functionalism revisited

• Cognitive systems researchers have very different perspectives, but in practice they are converging on some common questions

• Cognitive scientists would benefit from a common framework in which to discuss common interests and compare different designs (natural and artificial)

• Is a functionalist perspective a practical foundation for productive conversations??

Other stuff

Provide bridging tools

Abstract functions,“components”

ConcreteImplementations

Promote communication

http://neurocogblog.blogspot.com/

The “bifocal view”• How do states of consciousness fit into

neuroscience (since they seem to be created by the brain) and into psychology (since they seem to be related to behaviour)?

• Today’s dominant view is functionalism: the (input-output) relationships that hold between a behaving organism and the environment in which it behaves

• To achieve an understanding of how activity in the brain can relate [input to output] one has to consider … the central nervous system … as falling simultaneously under the laws of physics and chemistry and under those of cybernetics (or ‘information processing’)

Jeffrey Gray

Consciousness: Creeping up on the hard problem

Thinking About Thinking• Introducing the Real Time Club Brain, Mind & Computing Forum

Lunch

Wednesday 12 May 12:00 to 14:00

Venue: National Liberal Club, Whitehall Place London SW1A 2HE

http://www.realtimeclub.org/index.php?option=com_rtcmeetings&detail=46&Itemid=8&LinkedIn=dC

The relationship between neurophysiology (ie structure and biochemistry of the brain) and cognition (ie how we think and experience the world) is central to every aspect of our lives, yet one of the least understood areas of science. This will be a very important area of study over the coming decades, and is already producing research and debate on issues such as biological bases for criminality and antisocial behaviour (including use of evidence of tendency to such behaviour in court) and use of drugs that can enhance cognitive performance (e.g. nicotine and ritalin). Modern digital computing techniques will be crucial to research on the linkages of neurophysiology and cognition, as has been the case with recent tremendous advances in genetic research.







Theories of high level cognition in natural and artificial ... · cognition: circa 1970-1990...

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