事例ベースの意思決定理論<br>A Theory of Case-Based Decisions

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事例ベースの意思決定理論
A Theory of Case-Based Decisions

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 199 p.
  • 言語 ENG
  • 商品コード 9780521003117
  • DDC分類 658.4033

基本説明

Provides a new paradigm for modeling decision making under uncertainty.

Full Description


Gilboa and Schmeidler provide a paradigm for modelling decision making under uncertainty. Unlike the classical theory of expected utility maximization, case-based decision theory does not assume that decision makers know the possible 'states of the world' or the outcomes, let alone the decision matrix attaching outcomes to act-state pairs. Case-based decision theory suggests that people make decisions by analogies to past cases: they tend to choose acts that performed well in the past in similar situations, and to avoid acts that performed poorly. It is an alternative to expected utility theory when both states of the world and probabilities are neither given in the problem nor can be easily constructed. The authors describe the general theory and its relationship to planning, repeated choice problems, inductive inference, and learning; they highlight its mathematical and philosophical foundations and compare it with expected utility theory as well as with rule-based systems.

Table of Contents

Acknowledgments                                    x
1 Prologue 1 (28)
The scope of this book 1 (3)
Meta-theoretical vocabulary 4 (18)
Theories and conceptual frameworks 4 (4)
Descriptive and normative theories 8 (4)
Axiomatizations 12 (4)
Behaviorist, behavioral, and cognitive 16 (1)
theories
Rationality 17 (2)
Deviations from rationality 19 (1)
Subjective and objective terms 20 (2)
Meta-theoretical prejudices 22 (7)
Preliminary remark on the philosophy of 22 (1)
science
Utility and expected utility ``theories'' 23 (2)
as conceptual frameworks and as theories
On the validity of purely behavioral 25 (2)
economic theory
What does all this have to do with CBDT? 27 (2)
2 Decision rules 29 (33)
Elementary formula and interpretations 29 (18)
Motivating examples 29 (5)
Model 34 (5)
Aspirations and satisficing 39 (4)
Comparison with EUT 43 (3)
Comments 46 (1)
Variations and generalizations 47 (6)
Average similarity 47 (2)
Act similarity 49 (3)
Case similarity 52 (1)
CBDT as a behaviorist theory 53 (6)
W-maximization 53 (2)
Cognitive specification: EUT 55 (1)
Cognitive specification: CBDT 56 (1)
Comparing the cognitive specifications 57 (2)
Case-based prediction 59 (3)
3 Axiomatic derivation 62 (29)
Highlights 62 (2)
Model and result 64 (9)
Axioms 65 (2)
Basic result 67 (1)
Learning new cases 68 (1)
Equivalent cases 69 (2)
U-maximization 71 (2)
Discussion of the axioms 73 (4)
Proofs 77 (14)
4 Conceptual foundations 91 (18)
CBDT and expected utility theory 91 (7)
Reduction of theories 91 (2)
Hypothetical reasoning 93 (2)
Observability of data 95 (1)
The primacy of similarity 96 (1)
Bounded rationality? 97 (1)
CBDT and rule-based systems 98 (11)
What can be known? 98 (2)
Deriving case-based decision theory 100(5)
Implicit knowledge of rules 105(2)
Two roles of rules 107(2)
5 Planning 109(16)
Representation and evaluation of plans 109(10)
Dissection, selection, and recombination 109(3)
Representing uncertainty 112(2)
Plan evaluation 114(4)
Discussion 118(1)
Axiomatic derivation 119(6)
Set-up 119(2)
Axioms and result 121(2)
Proof 123(2)
6 Repeated choice 125(21)
Cumulative utility maximization 125(11)
Memory-dependent preferences 125(2)
Related literature 127(2)
Model and results 129(4)
Comments 133(1)
Proofs 134(2)
The potential 136(10)
Definition 136(2)
Normalized potential and neo-classical 138(3)
utility
Substitution and complementarity 141(5)
7 Learning and induction 146(43)
Learning to maximize expected payoff 146(28)
Aspiration-level adjustment 146(1)
Realism and ambitiousness 147(3)
Highlights 150(3)
Model 153(3)
Results 156(2)
Comments 158(3)
Proofs 161(13)
Learning the similarity function 174(9)
Examples 174(3)
Counter-example to U-maximization 177(4)
Learning and expertise 181(2)
Two views of induction: CBDT and simplicism 183(6)
Wittgenstein and Hume 183(1)
Examples 184(5)
Bibliography 189(8)
Index 197