Although valued for its ability to allow teams to collaborate and foster coalitional behaviors among the participants, game theory’s application to networking systems is not without challenges. Distributed Strategic Learning for Wireless Engineers illuminates the promise of learning in dynamic games as a tool for analyzing network evolution and underlines the potential pitfalls and difficulties likely to be encountered.
Establishing the link between several theories, this book demonstrates what is needed to learn strategic interaction in wireless networks under uncertainty, randomness, and time delays. It addresses questions such as:
The book provides an explicit description of how players attempt to learn over time about the game and about the behavior of others. It focuses on finite and infinite systems, where the interplay among the individual adjustments undertaken by the different players generates different learning dynamics, heterogeneous learning, risk-sensitive learning, and hybrid dynamics.
"synopsis" may belong to another edition of this title.
Hamidou Tembine
Establishing the link between several theories, this book demonstrates what is needed to learn strategic interaction in wireless networks under uncertainty, randomness, and time delays. This robust game theory cookbook analyzes games where some parameters are uncertain and random. Starting with the fundamentals of strategic learning and game theory, the text then covers partially and fully distributed learning, combined learning for negotiation, bargaining solutions, Nash equilibria, Stackelberg solutions, correlated equilibria, conjectural variations, and satisfactory solutions. It concludes with practical algorithms and techniques to implement game theory in wireless networks.
"About this title" may belong to another edition of this title.
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