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.
Preface
Part I : Strategic Learning
Chapter 1 : A Short Introduction to Game Theory
Chapter 2 : A Short Overview of Strategic Learning
Part II : Strategy or Payoff-Based Learning
Chapter 3 : Partially Distributed Strategy Learning
Chapter 4 : Fully Distributed Strategy Learning
Chapter 5 : Payoff Learning and Estimations
Part III : Combined Learning
Chapter 6 : Combined Learning in Dynamic Robust Games
Chapter 7 : Learning Under Unknown Payoffs and Delayed Measurement
Chapter 8 : Learning in Constrained Wireless Games
Chapter 9 : Hybrid Strategic Learning
Chapter 10 : Distributed Learning in Large-scale Systems
Chapter 11 : Learning in Stochastic Games
Index
