Table Of ContentMacmillan ComputerScience Series
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A. Abdellatif,J. Le Bihan, M.Limame, Oracle- A User'sGuide
Ian O. Angell, High-resolution ComputerGraphics UsingC
Ian O. Angelland Gareth Griffith, High-resolution Computer Graphics Using FORTRAN77
Ian O.Angell and Gareth Griffith, High-resolution ComputerGraphics UsingPascal
M. Azmoodeh, Abstract Data Types and Algorithms,secondedition
C. Bamford and P.Curran, Data Structures, Filesand Databases,secondedition
P. Beynon-Davies, Information Systems Development, secondedition
G.M. Birtwistle, Discrete Event Modelling on Simula
RichardBornat, Understanding and Writing Compilers
Linda E.M. Brackenbury, Design ofVLSISystems- A PracticalIntroduction
Alan Bradley, Peripheralsfor Computer Systems
G.R. Brookes and A.J. Stewart, Introduction to occam2 onthe Transputer
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Robert Cole, Computer Communications,secondedition
Eric Davaloand PatrickNairn, NeuralNetworks
S.M. Deen, Principles and Practice ofDatabase Systems
C.Delannoy, Turbo PascalProgramming
Tim Denvir, Introduction to Discrete Mathematicsfor Software Engineering
D. Englandet al.,A Sun User's Guide,secondedition
Jean Ettinger, Programming in C++
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Michel Gauthier, Ada - A Professional Course
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A.M. Listerand R.D. Eager, Fundamentals ofOperating Systems,fifth edition
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Ian Prall, ArtificialIntelligence
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Tony Royce,Structured COBOL- An Introduction
Artificial Intelligence
Ian Pratt
Department ofComputer Science
University ofManchester
M
MACMILLAN
© Ian Pratt 1994
All rights reserved. No reproduction, copy or transmission of
this publication may be made without written permission.
No paragraph ofthis publication may be reproduced, copied or
transmitted save with written permission or in accordance with
the provision ofthe Copyright, Designs and Patents Act 1988,
or under the terms ofany licence permitting limited copying
issued by the Copyright Licensing Agency, 90 Tottenham Court
Road, London WIP 9HE.
Any person who does any unauthorised act in relation to this
publication may beliable to criminal prosecution and civil
claims for damages.
First published 1994by
THE MACMILLAN PRESS LTD
Houndmills, Basingstoke, Hampshire RG21 2XS
and London
Companies and representatives
throughout the world
ISBN 978-0-333-59755-2 ISBN 978-1-349-13277-5 (eBook)
DOI 10.1007/978-1-349-13277-5
A catalogue record for this book is available
from the British Library.
Contents
Preface vii
1 WhatisArtificialIntelligence? 1
1.1 Introduction I
1.2 Asimpleplanningproblem 3
1.3 Inferenceoutsideplanning 10
1.4 Inference 13
1.5 Conclusion 15
2 Search and Planning 17
2.1 TheplanningprogramforBob 17
2.2 Workingon goalsseparately 28
2.3 Forwardand backwardchaining 29
2.4 Interactingplansand means-ends analysis 32
2.5 SearchinGame-Playing 39
2.6 Conclusion 46
3 LogicandInference 49
3.1 Logicand inference 49
3.2 AsimpleAI problem 51
3.3 Theframeproblem 55
3.4 An alternativeto logic 57
3.5 Closedworldassumptionsand theirproblems 60
3.6 Conclusion 62
4 ClosedWorldAssumptions 65
4.1 Aclosedworldassumption 65
4.2 p-minimalmodelsand predicatecircumscription 67
4.3 (p,p)-minimalmodelsandformulacircumscription 72
4.4 Backto the blocksworld 76
4.5 Nonmonotoniclogics 79
4.6 Conclusion 83
5 DefeasibleInference 85
5.1 PropertyInheritance 85
5.2 Problematiccases 89
5.3 Defaultlogic 93
5.4 Propertyinheritanceanddefault logic 97
5.5 Gerrymanderedcategories 100
5.6 Thereliabilityofpropertyinheritance 100
5.7 Asceptical solution 102
v
vi Contents
6 ReasonMaintenance 108
6.1 The ideaofreasonmaintenance 108
6.2 Doyle'sTMS 109
6.3 Circularjustifications 123
6.4 TMS'sanddefaultlogic 130
6.5 Assumption-basedTMS's 131
6.6 Conclusion:defeasible reasoningand reason maintenance 136
7 MemoryOrganization 140
7.1 The needformemoryorganization 140
7.2 Scripts 142
7.3 Frames 150
7.4 Scriptacquisitionandconceptformation 154
7.5 Conclusion 158
8 Probabilistic Inference 161
8.1 Subjectiveprobability 161
8.2 Conditionalprobability 164
8.3 Some basicresultsofprobabilitytheory 165
8.4 Probability,causationandBayesnetworks 168
8.5 ComputingprobabilitieswithBayesnetworks 172
9 Induction 182
9.1 Introduction 182
9.2 Aframeworkforinductiveinference 183
9.3 Monomialinductionprocedures 186
9.4 The choiceofinductivebiasandthejustificationofinduction 199
9.5 103 200
9.6 Inductionandprobability 207
9.7 Grue 212
10 NeuralNetworks 216
10.1 The perceptron 216
10.2 Feed-forward,multi-layernetworks 224
10.3 HopfieldNets 234
10.4 Distributedrepresentations 241
Appendix: ThePredicateCalculus 246
A.1 Introduction 246
A.2 The propositionalcalculus: syntax, semantics and prooftheory 246
A.3 Predicatecalculus: syntax,semanticsand prooftheory 258
Index 275
Preface
Aroughdefinitionofartificialintelligencemightbe: theenterpriseofprogramming
computersto reason. Forinstance,anintelligentcomputerinterfacewouldbeone
which reasoned about its user's commands so as to interpret them sensibly and
flexibly; and an intelligent robot would be one which could reason about novel
ways to carry out its tasks in a changing environment. Indeed, is hard to see
what intelligencewithoutreasoningcould be, and hard tosee how,in practice,an
artificialdevicecouldbe madeto reason withoutbeingcontrolledby somesortof
computer.
As such, AI is, and needs to be, a highly technical discipline. It traffics in
symbolsand formulae,logicsand computerlanguages,theorems and algorithms.
Computersbrookno vaguenessor hand waving: thetheoryofreasoningrequired
by AI must therefore be a theory more precise and detailed than any that has
gonebefore. Yetit wouldbe a mistake to thinkthat AI is a disciplineconcerned
primarily with computers. For what makes AI so challenging (and at the same
time so fascinating) has less to do with the computers in whichit hopes one day
to produce intelligence, than with the mystery ofwhat, exactly, the intelligence
it hopes to produce in them is. That is, the problems of AI are not primarily
computingproblems (hardware or software), but problems concerning what it is
for a device to reason. And the most valuablecontributionsmade by AI are not
primarily contributions to computing technology, but the precise expression of
insightsintothe verynatureofthoughtitself.
Thus, a textbook on AI should have two main aims: first, to explain the
technicaldetailsbehindthe most importantadvances in thesubject,and second,to
explainthe essentialinsightsinto thenatureofthoughtwhich theyexpress. These
are the aims ofthis book.
The material presented in the following pages derives from courses given at
the University ofManchester (both at undergraduate- and MSc-level) and at the
UniversitlitHildesheim. Itisdesignedprimarilyforuniversitycourses inAI which
aimto take the studenttoa level where alargeproportionofarticles inthejournal
Artificial Intelligence are accessible. The book is thus suitable for AI courses
from the 2nd year onwards (forstudents specializing in AI) up to master's level
(forstudentsencountering AI for the first time). Thus,this book covers material
at a greater level ofsophistication than is normal for AI textbooks. At the same
vii
viii Preface
time, thebook isself-containedinthatitpresupposesonly aminimal background
in mathematics and computing. In particular, the appendix contains a tutorial
introductiontologic.
Eachchapter contains suggestions for furtherreading, and there isaselection
ofexercises which vary from the routine to the very challenging. No reliance is
made on any specific programming language, although some exercises concern
computerimplementationsofalgorithmsdiscussedin thetext. Chapters 1-6form
the coreof thebook,and arebest tackled inorder; chapters7-10, bycontrast, are
more independent,and readers maychoose to skipone or more ofthem. Having
gone ratherdeeper into many issues than othercurrently available AI textbooks,
I have had to be more selective in the topics covered. My response has been
to ignore natural language processing, computer vision and motor control. The
justification for this selection is purely pragmatic. The omitted topics rely on
specialized backgroundknowledge inlinguisticsorappliedmathematics,and are,
Ibelieve,best treatedinspecialist books.
Finally,Ihaveanumberofacknowledgementstomake. MystayinHildesheim,
whereIwasprivilegedtoteachsomeofthismaterial, wasmadepossiblebyagrant
from the DeutscherAkademischer Austauschdienst, as well as by the efforts of
various members of staff there. Much ofthe writing was done duringsabbatical
leave fromManchester atthe Max Planck InstitutfUrInformatikin SaarbrUcken.
Iam indebtedto theDepartment ofComputerScience at Manchester University,
to the Royal Society for funding this sabbatical, and ofcourse to my erstwhile
colleagues in Saarbrucken for their overwhelming hospitality and friendliness.
In addition, progress on this book was aided by a research grant from the Joint
Councils'Research InitiativeinCognitiveScience,no. SPG8920254. Iwishalso
to express my gratitude to the following individuals for their help: John Stobo,
David Bree,Jens Dorpmund, Detlev Fehrer, ChiaraMenchini, Luoping Xu, Jeff
Paris,AndrzejGlowinski,IvanLeudar and Vaughan Marks. Finally, Iwouldlike
tothankmylong-sufferingstudents, both in the UKand inGermany, for beingso
patient while I was trying out a variety of idem;on them, only some of which I
have thoughtitwisetoprint.
1 What is Artificial Intelligence?
1.1 Introduction
Imagine you are at home, sitting in an armchair, when you notice that it is un
comfortably hot. You walk over to the central heating control and look at the
thermometer. "30°C," itsays. Youturn thetemperature control knobdownafew
notchesand returntoyourseat, confidentthatthetemperaturewillfall. Now con
siderthingsfrom thethermostat'spointofview. Ithadbeen settokeeptheheating
at 30°C, and was busily switching the heaters on or offdepending on whether
the thermometerregistered less thanor more than 30°C. After youtum itdown a
coupleofnotches, itdoes exactly thesame thingbutforsome lowertemperature.
Insomerespects,youandthethermostathavemuchincommon. Thethermostat
is set to a temperature which it is its job to maintain. It is so wired-up to the
thermometerand the heatingsystem thatadrop intemperaturebelowtheset level
causes the heatingtocome on, andariseabove that levelcauses theheatingtogo
off. Youtoo might be said towanttomaintain acertain levelofcomfortregarding
how hotorcold you feel (this intum maydepend onanumberoffactors). Youare
so wired-up that ifyou become uncomfortablycold, you tum theheating control
knob upa few notches;and ifyou become uncomfortablyhot,youturnitdown.
So much for thesimilaritiesbetween youandthethermostat;nowforacrucial
difference. Althoughboth the thermostat and youreact tochanges intemperature
so as tocontrolthem, onlyyou haveanyideaofwhatyou aredoing,and why you
aredoingit. Youwanttomake thingscooler,believethatturning theheating down
has thiseffect, and inferor decidethatthethingtodois tooperate the appropriate
control. But the thermostat (according to conventionalwisdom) does not wantor
believeor inferor decideanything: itjust switches from one stateto another; it
isjust so wired-up that changes in temperature cause correctivereaction by the
heatingsystem. Whileyou reason, thethermostatjust switches.
The foregoing observations leave us with something ofa puzzle. When you
walkovertoadjust theheatingcontrol-again,according toconventionalwisdom
yourmovementsarecaused, insofarastheyarecausedatall,byphysicalprocesses
in your brain. True, these physical processes ofinferringand deciding, like the
physical states of believingand desiring on which they depend, are incredibly
complex affairs. But they are stilljust physical processes and states. True again,
the 'wiring'connectingthe nerve cellsinyourskin, viayour brain,tothemuscles
