Econophysics of the Kolkata Restaurant problem and related games: classical and quantum strategies for multi-agent, multi-choice repetitive games

Preface -- Acknowledgements -- Contents -- 1 Introduction -- 1.1 Background -- 1.1.1 Minority Game -- 1.1.2 Kolkata Restaurant Problem -- 1.2 Motivation of the Book -- 1.3 Plan of the Book -- 2 Kolkata Paise Restaurant Problem -- 2.1 Introduction -- 2.2 Stochastic Learning Strategies -- 2.2.1 Random Choice Strategies -- 2.2.2 Rank Dependent Strategies -- 2.2.3 Strict Crowd-Avoiding Case -- 2.2.4 Stochastic Crowd Avoiding Case -- 2.3 Convergence to a Fair Social Norm with Deterministic Strategies -- 2.3.1 A `Fair' Strategy -- 2.3.2 Asymptotically Fair Strategy -- 2.4 Summary and Discussion -- 3 Phase Transition in the Kolkata Paise Restaurant Problem -- 3.1 Introduction -- 3.2 The Models -- 3.3 Results from Numerical Simulations -- 3.3.1 Model A -- 3.3.2 Model B -- 3.4 Analytical Treatment of the Models in Mean Field Case -- 3.4.1 Approximate Analysis of the Critical Point and Faster-Is-Slower Effect -- 3.4.2 Analysis of the Finite Size Effects on the Time to Reach the Absorbing State -- 3.5 Summary and Discussions -- 4 Zipf's Law from Kolkata Paise Restaurant Problem -- 4.1 Introduction -- 4.2 Model -- 4.3 Results -- 4.3.1 Distribution of Sizes -- 4.3.2 Utilization -- 4.3.3 Evolution with Fitness -- 4.4 Empirical Evidences -- 4.5 Summary and Discussions -- 5 Minority Game and Kolkata Paise Restaurant Problem -- 5.1 Introduction -- 5.2 Strategy of the Agents -- 5.2.1 Uniform Approximation in Guessing the Excess Crowd -- 5.2.2 Nonuniform Guessing of the Excess Crowd -- 5.2.3 Following an Annealing Schedule -- 5.3 Effect of Random Traders -- 5.4 Summary and Discussions -- 6 From Classical Games, the Kokata Paise Restuarant Game, to Quantum Games -- 6.1 A Short Introduction to Classical Games -- 6.1.1 Definitions and Preliminaries -- 6.1.2 Repeated Games -- 6.1.3 Games and Evolution Theory -- 6.2 KPR -- 6.2.1 Some Simple KPR Results