In our day-to day-lives we constantly make decisions that are simply "good enough" rather than optimal. This may be to save time and trouble, or, for example, to avoid conflict with colleagues. Most computer-based decision-making algorithms, on the other hand, doggedly seek the optimal solution base
Satisficing Games and Decision Making: With Applications to Engineering and Computer Science
β Scribed by Wynn C. Stirling
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No coin nor oath required. For personal study only.
β¦ Table of Contents
Half-title
Title
Copyright
Dedication
Contents
Figures
Tables
Preface
1 Rationality
1.1 Games machines play
1.2 Conventional notions
1.2.1 Substantive rationality
1.2.2 Procedural rationality
1.2.3 Bounded rationality
1.3 Middle ground
1.3.1 Adequacy
1.3.2 Sociality
2 Locality
2.1 Localization concepts
2.2 Group rationality
2.3 Conditioning
2.4 Emergence
2.5 Less is more
3 Praxeology
3.1 Dichotomies
3.1.1 Costβbenefit analysis
3.1.2 Epistemic utility theory
3.2 Abduction
3.3 Epistemic games
3.3.1 The information-conservation game
3.3.2 The error-avoidance game
3.3.3 Leviβs epistemic game
3.4 Praxeic utility
3.5 Tie-breaking
3.6 Praxeology versus Bayesianism
4 Equanimity
4.1 Equilibria
4.2 Adequacy
4.3 Consistency
5 Uncertainty
5.1 Bayesian uncertainty
5.2 Imprecision
5.3 Equivocation
5.3.1 Attitude
Tension
5.4 Quasi-invariance
6 Community
6.1 Joint and individual options
6.2 Interdependency
6.2.1 Mixtures
6.2.2 Conditioning
6.2.3 Spatial emergence
6.3 Satisficing games
6.4 Group preference
6.5 Optimizing versus satisficing
7 Congruency
7.1 Classical negotiation
7.2 Satisficing negotiation
7.2.1 The negotiation theorem
7.2.2 The Resource Sharing game
7.2.3 Intrinsic decisions
7.3 Social welfare
7.3.1 Arrowian social welfare
7.3.2 Satisficing social welfare
8 Complexity
8.1 Game examples
8.1.1 Bluffing
8.1.2 Battle of the Sexes
8.1.3 Prisonerβs Dilemma
8.1.4 The Ultimatum game
8.1.5 The game-theoretic role of social relationships
8.2 Mitigating complexity
Hierarchical
Markovian
8.3 An N-player example
8.3.1 The optimal solution
8.3.2 The satisficing solution
9 Meliority
9.1 Amelioration versus optimization
9.2 Meta-decisions
9.3 Some open questions
9.4 The enterprise of synthesis
Appendix A: Bounded rationality
Appendix B: Game theory basics
Appendix C: Probability theory basics
Appendix D: A logical basis for praxeic reasoning
D.1 Desiderata for coherent evaluation
D.2 Quantitative rules of behavior
D.3 Constructing probability (selectability, rejectability)
Bibliography
Name index
Subject index
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