Reciprocity, Evolution, and Decision Games in Network and Data Science

Description

Learn how to analyse and manage evolutionary and sequential user behaviours 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 behaviour, 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. Cover Summary Title Page Contents Preface 1 Basic Game Theory Part I: Indirect Reciprocity 2 Indirect Reciprocity Game in Cognitive Networks 3 Indirect Reciprocity Game for Dynamic Channel Access 4 Multiuser Indirect Reciprocity Game for Cooperative Communications 5 Indirect Reciprocity Data Fusion Game and Application to Cooperative Spectrum Sensing Part II: Evolutionary Games 6 Evolutionary Game for Cooperative Peer-to-Peer Streaming 7 Evolutionary Game for Spectrum Sensing and Access in Cognitive Networks 8 Graphical Evolutionary Game for Distributed Adaptive Networks 9 Graphical Evolutionary Game for Information Diffusion in Social Networks 10 Graphical Evolutionary Game for Information Diffusion in Heterogeneous Social Networks Part III: Sequential Decision-Making 11 Introduction to Sequential Decision-Making 12 Chinese Restaurant Game: Sequential Decision-Making in Static Systems 13 Dynamic Chinese Restaurant Game: Sequential Decision-Making in Dynamic Systems 14 Indian Buffet Game for Multiple Choices 15 Hidden Chinese Restaurant Game: Learning from Actions 16 Wireless Network Access with Mechanism Design 17 Deal Selection on Social Media with Behavior Prediction 18 Social Computing: Answer vs. Vote Index