| Description |
1 online resource (xv, 457 pages) : illustrations |
| Contents |
Cover -- Half-title -- Title page -- Copyright information -- Contents -- Preface -- 1 Basic Game Theory -- 1.1 Strategic-Form Games and Nash Equilibrium -- 1.2 Extensive-Form Games and Subgame-Perfect Nash Equilibrium -- 1.3 Incomplete Information: Signal and Bayesian Equilibrium -- 1.4 Repeated Games and Stochastic Games -- Part I Indirect Reciprocity -- 2 Indirect Reciprocity Game in Cognitive Networks -- 2.1 Introduction -- 2.2 The System Model -- 2.2.1 Social Norms -- 2.2.2 Action Rules -- 2.3 Optimal Action Rule -- 2.3.1 Reputation Updating Policy |
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2.3.2 Stationary Reputation Distribution -- 2.3.3 Payoff Function -- 2.3.4 Optimal Action Using an Alternative Algorithm -- 2.4 Action Spreading Due to Natural Selection -- 2.4.1 Action Spreading Algorithm Using the Wright-Fisher Model -- 2.4.2 Action Spreading Algorithm Using the Replicator Dynamic Equation -- 2.5 Evolutionarily Stable Strategy and Simulations -- 2.5.1 Binary Reputation Scenario -- 2.5.2 Multilevel Reputation Scenario -- 2.6 Conclusion -- References -- 3 Indirect Reciprocity Game for Dynamic Channel Access -- 3.1 Introduction -- 3.2 System Model -- 3.2.1 Action |
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3.2.2 Social Norm: How to Assign Reputation -- 3.2.3 Power Level and Relay Power -- 3.2.4 Channel Quality Distribution -- 3.3 Theoretical Analysis -- 3.3.1 Reputation Updating Policy -- 3.3.2 Power Detection and Power Detection Transition Matrix -- 3.3.3 Stationary Reputation Distribution -- 3.3.4 Payoff Function and Equilibrium of the Indirect Reciprocity Game -- 3.3.5 Stability of the Optimal Action Rule -- 3.4 Simulation -- 3.4.1 Evolutionary Stability of Optimal Action a[sub(2) sup(*)] -- 3.4.2 System Performance -- 3.4.3 Different Social Norms -- 3.5 Conclusion -- References |
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4 Multiuser Indirect Reciprocity Game for Cooperative Communications -- 4.1 Introduction -- 4.2 System Model -- 4.2.1 Physical Layer Model with Relay Selection -- 4.2.2 Incentive Schemes Based on the Indirect Reciprocity Game -- 4.2.3 Overheads of the Scheme -- 4.2.4 Payoff Functions -- 4.3 Steady-State Analysis Using Markov Decision Processes -- 4.3.1 Stationary Reputation Distribution -- 4.3.2 Long-Term Expected Payoffs at Steady States -- 4.3.3 Equilibrium Steady State -- 4.4 Evolutionary Modeling of the Indirect Reciprocity Game -- 4.4.1 Evolutionary Dynamics of the Indirect Reciprocity Game |
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4.4.2 Evolutionarily Stable Strategy -- 4.5 Energy Detection -- 4.6 Simulation Results -- 4.7 Discussion and Conclusion -- References -- 5 Indirect Reciprocity Data Fusion Game and Application to Cooperative Spectrum Sensing -- 5.1 Introduction -- 5.2 Indirect Reciprocity Data Fusion Game -- 5.2.1 System Model -- 5.2.2 Action and Action Rule -- 5.2.3 Social Norm: How to Assign Reputation -- 5.2.4 Decision Consistency Matrix -- 5.2.5 Reputation Updating Policy -- 5.2.6 Payoff Function -- 5.2.7 Equilibrium of the Indirect Reciprocity Data Fusion Game |
| Summary |
"Learn how to analyze and manage evolutionary and sequential user behaviors in modern networks, and how to optimize network performance by using indirect reciprocity, evolutionary games, and sequential decision-making. Understand the latest theory without the need to go through the details of traditional game theory. With practical management tools to regulate user behavior and simulations and experiments with real data sets, this is an ideal tool for graduate students and researchers working in networking, communications, and signal processing"-- Provided by publisher |
| Bibliography |
Includes bibliographical references and index |
| Notes |
Description based on online resource; title from digital title page (viewed on October 12, 2021) |
| Subject |
Game theory.
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System analysis.
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systems analysis.
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COMPUTERS / Database Administration & Management.
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Game theory
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System analysis
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| Form |
Electronic book
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| Author |
Wang, Chih-Yu, 1984- author.
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Jiang, Chunxiao, 1987- author.
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Liu, K. J. Ray, 1961- author.
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| LC no. |
2021019447 |
| ISBN |
9781108859783 |
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110885978X |
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