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Artificial Intelligence PDF

289 Pages·1994·28.935 MB·English
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Macmillan ComputerScience Series Consulting Editor: Professor F.H.Sumner, Universityof Manchester 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 P.C.Capon and P.J. 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Addyman, A Practical Introduction to Pascal,secondedition continued overleaf Other titles Roy Anderson, Management,InformationSystemsandComputers Ian O.Angelland DimitriosTsoubelis, AdvancedGraphicson VGA and XGA Cards Using Borlandc++ B.V.Cordingleyand D. Chamund, AdvancedBASICScientific Subroutines N. Frude, A GuidetoSPSS/PC+,secondedition PercyMelt, Introductionto Computing Tony Royce,COBOL- AnIntroduction 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

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