Decision Theory with a Human Face

350 Pages·2017·2.583 MB·English

by  Richard Bradley

DecisionTheorywithaHumanFace
When making decisions, people naturally face uncertainty about the
potentialconsequencesoftheiractionsdueinparttolimitsintheircapacity
to represent, evaluate or deliberate. Nonetheless, they aim to make the
best decisions possible. In Decision Theory with a Human Face, Richard
Bradley develops new theories of agency and rational decision making,
offeringguidanceonhow‘real’agentswhoareawareoftheirboundsshould
represent the uncertainty they face, how they should revise their opinions
asaresultofexperienceandhowtheyshouldmakedecisionswhenlacking
fullawarenessof,orpreciseopinionson,relevantcontingencies.Heengages
with the strengths and flaws of Bayesian reasoning, and presents clear and
comprehensiveexplorationsofkeyissuesindecisiontheory,frombeliefand
desiretosemanticsandlearning.Hisbookdrawsonphilosophy,economics,
decision science and psychology and will appeal to readers in all these
disciplines.
Richard Bradley is Professor of Philosophy at the London School of Eco-
nomics and Political Science. He is an editor of the journal Economics and
Philosophy, and his work on decision theory, semantics and epistemology
hasbeenpublishedinnumerousleadingjournals.

Decision Theory with a Human Face
RICHARD BRADLEY
LondonSchoolofEconomicsandPoliticalScience
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Informationonthistitle:www.cambridge.org/9781107003217
DOI:10.1017/9780511760105
(cid:2)c RichardBradley2017
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Firstpublished2017
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LibraryofCongressCataloging-in-PublicationData
Names:Bradley,Richard,1964December13–author.
Title:Decisiontheorywithahumanface/RichardBradley,London
SchoolofEconomicsandPoliticalScience.
Description:Cambridge:CambridgeUniversityPress,2018.|
Includesbibliographicalreferencesandindex.
Identifiers:LCCN2017032958|ISBN9781107003217(hardback:alk.paper)
Subjects:LCSH:Bayesianstatisticaldecisiontheory.|Decision
making–Mathematicalmodels.|Uncertainty–Mathematicalmodels.
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For Shura

Contents
ListofFigures pagex
ListofTables xi
Preface xiii
Introduction 1
parti rationality,uncertaintyandchoice 7
1 DecisionProblems 9
1.1 MaximisationofExpectedBenefit 9
1.2 FramingDecisions 13
1.3 Savage’sTheory 16
2 Rationality 21
2.1 ModerateHumeanism 21
2.2 TheChoicePrinciple 24
2.3 Subjectivism 27
3 Uncertainty 31
3.1 EvaluativeUncertainty 32
3.2 OptionUncertainty 35
3.3 ModalUncertainty 39
4 JustifyingBayesianism 41
4.1 Pragmatism 42
4.2 InterpretationsofPreference 45
4.3 RepresentationTheorems 47
4.4 Savage’sRepresentationTheorem 49
4.5 EvaluationofSavage’sAxioms 54
4.6 EvaluationofSavage’sArgument 59
vii
viii Contents
partii prospectiverationality 63
5 RationalBeliefandDesire 65
5.1 Agents 65
5.2 Prospects 66
5.3 Attitudes 71
5.4 RationalBeliefandDesire 77
5.5 AspirationsofObjectivity 85
6 ConditionalAttitudes 89
6.1 Suppositions 90
6.2 SuppositionalProbabilityandDesirability 92
6.3 EvidentialSupposition 95
6.4 Independence 98
6.5 Foundations* 99
6.6 HypotheticalReasoning 104
7 ConditionalsandtheRamseyTest 109
7.1 TheRamseyTestforBelief 109
7.2 TheRamseyTestforDesire 111
7.3 ChancesandCounterfactuals 113
7.4 Foundations 116
7.5 FacingtheTrivialityResults 118
7.6 PartitioningConditionals 122
7.7 Summary 125
partiii facingtheworld 127
8 MultidimensionalPossible-WorldSemantics 129
8.1 ProspectsandPossibleWorlds 129
8.2 MultidimensionalSemantics 136
8.3 Probability 142
8.4 DesirabilityandCounterfactualValue 146
8.5 ValueActualism 149
8.6 PartitioningConditionals 152
8.7 ConcludingRemarks 155
9 TakingAction 157
9.1 DecisionPrinciples 157
9.2 Preference-BasedChoice 159
9.3 DecisionsunderRisk 162
9.4 DecisionMakingunderUncertainty 165
9.5 BayesianDecisionTheory 169
9.6 CausalDecisionTheory 177
Contents ix
10 TheLearningAgent 182
10.1 Introduction 182
10.2 ExperienceandLearning 185
10.3 ClassicalBayesianConditioning 188
10.4 JeffreyConditioning 192
10.5 AdamsConditioning 196
10.6 PreferenceChange 200
partiv rationalitywithinbounds 213
11 ImpreciseBayesianism 215
11.1 Introduction 215
11.2 BoundedMinds 216
11.3 ImpreciseBayesianism 223
11.4 SevereUncertainty 227
11.5 RationalIncompletePreference 232
11.6 ChallengestoImpreciseBayesianism 238
12 ChangingYourMind 242
12.1 AttitudeChange 243
12.2 ChanginganIncompleteStateofMind 244
12.3 Unawareness 252
12.4 ChangesinStatesofAwareness 256
13 DecisionMakingunderAmbiguity 262
13.1 Introduction 262
13.2 ReachingaJudgement 263
13.3 AlternativeDecisionRules 271
13.4 CautiousDecisionMaking 277
13.5 ModelsofAmbiguityAversion* 280
13.6 TheRationalityofAmbiguityAversion 283
13.7 ConcludingRemarks 286
14 Confidence 289
14.1 TheParadoxofIdealEvidence 289
14.2 Confidence-BasedLearning 293
14.3 AModelofConfidence 296
14.4 ConcludingRemarks 303
Appendix:Proofs 305
Bibliography 322
Index 331