Artificial Intelligence: Foundations of Computational Agents.

682 Pages·2010·4.38 MB·English

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Artificial Intelligence
Foundations of Computational Agents
Artificial Intelligence: Foundations of Computational Agents is about the science of
artificialintelligence(AI).ItpresentsAIasthestudyofthedesignofintelligentcom-
putational agents. The book is structured as a textbook, but it is accessible to a wide
audienceofprofessionalsandresearchers.
The past decades have witnessed the emergence of AI as a serious science and
engineering discipline. This book provides the first accessible synthesis of the field
aimed at undergraduate and graduate students. It provides a coherent vision of the
foundations of the field as it is today, in terms of a multidimensional design space
thathasbeenpartiallyexplored.Aswithanyscienceworthitssalt,AIhasacoherent,
formaltheoryandarambunctiousexperimentalwing.Thebookbalancestheoryand
experiment,showinghowtolinkthemintimatelytogether.Itdevelopsthescienceof
AItogetherwithitsengineeringapplications.
DavidL.PooleisProfessorofComputerScienceattheUniversityofBritishColumbia.
HeisacoauthorofComputationalIntelligence:ALogicalApproach(1998),cochairofthe
Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), and coeditor
of the Proceedings of the Tenth Conference in Uncertainty in Artificial Intelligence (1994).
Poole is a former associate editor of the Journal of Artificial Intelligence Research. He is
an associate editor of Artificial Intelligence and on the editorial boards of AI Magazine
and AAAI Press. He is the secretary of the Association for Uncertainty in Artificial
Intelligence and is a Fellow of the Association for the Advancement of Artificial
Intelligence.
Alan K. Mackworth is Professor of Computer Science and Canada Research Chair
inArtificialIntelligenceattheUniversityofBritishColumbia.Hehasauthoredmore
than100papersandcoauthoredthetextComputationalIntelligence:ALogicalApproach.
He was President and Trustee of International Joint Conferences on AI (IJCAI) Inc.
Mackworth was vice president and president of the Canadian Society for Compu-
tational Studies of Intelligence (CSCSI). He has served as president of the AAAI.
He also served as the founding director of the UBC Laboratory for Computational
Intelligence. He is a Fellow of the Canadian Institute for Advanced Research, AAAI,
andtheRoyalSocietyofCanada.

Artificial Intelligence
Foundations of Computational Agents
David L. Poole
UniversityofBritishColumbia
Alan K. Mackworth
UniversityofBritishColumbia
CAMBRIDGEUNIVERSITYPRESS
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Cambridge University Press
The Edinburgh Building, Cambridge CB2 8RU, UK
Published in the United States of America by Cambridge University Press, New York
www.cambridge.org
Information on this title: www.cambridge.org/9780521519007
© David L. Poole and Alan K. Mackworth 2010
This publication is in copyright. Subject to statutory exception and to the
provision of relevant collective licensing agreements, no reproduction of any part
may take place without the written permission of Cambridge University Press.
First published in print format 2010
ISBN-13 978-0-511-72946-1 eBook (NetLibrary)
ISBN-13 978-0-521-51900-7 Hardback
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and does not guarantee that any content on such websites is, or will remain,
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Toourfamiliesfortheirlove,support,andpatience
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Contents
Preface xiii
I AgentsintheWorld:WhatAreAgentsandHowCanTheyBe
Built? 1
1 ArtificialIntelligenceandAgents 3
1.1 WhatIsArtificialIntelligence? . . . . . . . . . . . . . . . . . . 3
1.2 ABriefHistoryofAI . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 AgentsSituatedinEnvironments . . . . . . . . . . . . . . . . . 10
1.4 KnowledgeRepresentation . . . . . . . . . . . . . . . . . . . . 11
1.5 DimensionsofComplexity . . . . . . . . . . . . . . . . . . . . . 19
1.6 PrototypicalApplications . . . . . . . . . . . . . . . . . . . . . 29
1.7 OverviewoftheBook . . . . . . . . . . . . . . . . . . . . . . . 39
1.8 Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
1.9 ReferencesandFurtherReading . . . . . . . . . . . . . . . . . 40
1.10 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2 AgentArchitecturesandHierarchicalControl 43
2.1 Agents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
2.2 AgentSystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.3 HierarchicalControl . . . . . . . . . . . . . . . . . . . . . . . . 50
2.4 EmbeddedandSimulatedAgents . . . . . . . . . . . . . . . . 59
2.5 ActingwithReasoning . . . . . . . . . . . . . . . . . . . . . . . 60
2.6 Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
vii
viii Contents
2.7 ReferencesandFurtherReading . . . . . . . . . . . . . . . . . 66
2.8 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
II RepresentingandReasoning 69
3 StatesandSearching 71
3.1 ProblemSolvingasSearch . . . . . . . . . . . . . . . . . . . . . 71
3.2 StateSpaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.3 GraphSearching . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.4 AGenericSearchingAlgorithm . . . . . . . . . . . . . . . . . . 77
3.5 UninformedSearchStrategies . . . . . . . . . . . . . . . . . . . 79
3.6 HeuristicSearch . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
3.7 MoreSophisticatedSearch . . . . . . . . . . . . . . . . . . . . . 92
3.8 Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
3.9 ReferencesandFurtherReading . . . . . . . . . . . . . . . . . 106
3.10 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
4 FeaturesandConstraints 111
4.1 FeaturesandStates . . . . . . . . . . . . . . . . . . . . . . . . . 111
4.2 PossibleWorlds,Variables,andConstraints . . . . . . . . . . . 113
4.3 Generate-and-TestAlgorithms . . . . . . . . . . . . . . . . . . 118
4.4 SolvingCSPsUsingSearch . . . . . . . . . . . . . . . . . . . . 119
4.5 ConsistencyAlgorithms . . . . . . . . . . . . . . . . . . . . . . 120
4.6 DomainSplitting . . . . . . . . . . . . . . . . . . . . . . . . . . 125
4.7 VariableElimination . . . . . . . . . . . . . . . . . . . . . . . . 127
4.8 LocalSearch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
4.9 Population-BasedMethods . . . . . . . . . . . . . . . . . . . . 141
4.10 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
4.11 Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
4.12 ReferencesandFurtherReading . . . . . . . . . . . . . . . . . 151
4.13 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
5 PropositionsandInference 157
5.1 Propositions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
5.2 PropositionalDefiniteClauses . . . . . . . . . . . . . . . . . . 163
5.3 KnowledgeRepresentationIssues . . . . . . . . . . . . . . . . 174
5.4 ProvingbyContradictions . . . . . . . . . . . . . . . . . . . . . 185
5.5 CompleteKnowledgeAssumption . . . . . . . . . . . . . . . . 193
5.6 Abduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199
5.7 CausalModels . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
5.8 Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206
5.9 ReferencesandFurtherReading . . . . . . . . . . . . . . . . . 207
5.10 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208