Table of contents

In this concise book based on his Arne Ryde Lectures in 2002, Young suggests a conceptual framework for studying strategic learning and highlights theoretical developments in the area. He discusses the interactive learning problem; reinforcement and regret; equilibrium; conditional no-regret learning; prediction, postdiction, and calibration; fictitious play and its variants; Bayesian learning; and hypothesis testing. Young's framework emphasizes the amount of information required to implement different types of learning rules, criteria for evaluating their performance, and alternative notions of equilibrium to which they converge. He also stresses the limits of what can be achieved: for a given type of game and a given amount of information, there may exist no learning procedure that satisfies certain reasonable criteria of performance and convergence. In short, Young has provided a valuable primer that delineates what we know, what we would like to know, and the limits of what we can know, when we try to learn about a system that is composed of other learners.

The Wisdom of Strategic Learning has enabled many organizations to develop a strategic approach to learning and development. Its premise that learning must be integrated with the strategic direction of the organization has been validated by numerous successful businesses which have implemented its tried and tested approaches. This second edition of Ian Cunningham's book updates and expands material on the importance of the self managed learning approach to create focused, active and committed employees. A new chapter on the role and development of staff in SML programmes has been added, along with new appendices, for example on selling the approach. With new case material including the use of online groups on the Internet, this practical, thought-provoking book shows how the ideas behind the learning organization can be applied for strategic advantage.

Spontaneous Order brings together Peyton Young's research on evolutionary game theory and its diverse applications across a wide range of academic disciplines, including economics, sociology, philosophy, biology, computer science, and engineering. Enhanced with an introductory essay and commentaries, the book pulls together the author's work thematically to provide a valuable resource for scholars of economic theory. Young argues that equilibrium behaviors often coalesce from the interactions and experiences of many dispersed individuals acting with fragmentary knowledge of the world, rather than (as is often assumed in economics) from the actions of fully rational agents with commonly held beliefs. The author presents a unified and rigorous account of how such 'bottom-up' evolutionary processes work, using recent advances in stochastic dynamical systems theory. This analytical framework illuminates how social norms and institutions evolve, how social and technical innovations spread in society, and how these processes depend on adaptive learning behavior by human subjects.

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: How much information is enough for effective distributed decision making? Is having more information always useful in terms of system performance? What are the individual learning performance bounds under outdated and imperfect measurement? What are the possible dynamics and outcomes if the players adopt different learning patterns? If convergence occurs, what is the convergence time of heterogeneous learning? What are the issues of hybrid learning? How can one develop fast and efficient learning schemes in scenarios where some players have more information than the others? What is the impact of risk-sensitivity in strategic learning systems? How can one construct learning schemes in a dynamic environment in which one of the players do not observe a numerical value of its own-payoffs but only a signal of it? How can one learn "unstable" equilibria and global optima in a fully distributed manner? 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.

The breadth of this work will allow the reader to acquire a comprehensive and panoramic picture of the nature of innovation within a single handbook.

What is Game Theory Game theory is the study of mathematical models of strategic interactions among rational agents. It has applications in many fields of social science, used extensively in economics as well as in logic, systems science and computer science. Traditional game theory addressed two-person zero-sum games, in which a participant's gains or losses are exactly balanced by the losses and gains of the other participant. In the 21st century, game theory applies to a wider range of behavioral relations, and it is now an umbrella term for the science of logical decision making in humans, animals, as well as computers. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Game theory Chapter 2: Evolutionarily stable strategy Chapter 3: Nash equilibrium Chapter 4: Chicken (game) Chapter 5: Coordination game Chapter 6: Centipede game Chapter 7: Strategy (game theory) Chapter 8: Non-cooperative game theory Chapter 9: Backward induction Chapter 10: Symmetric game Chapter 11: Folk theorem (game theory) Chapter 12: Correlated equilibrium Chapter 13: Outcome (game theory) Chapter 14: Peyton Young Chapter 15: Subgame perfect equilibrium Chapter 16: Quantal response equilibrium Chapter 17: Epsilon-equilibrium Chapter 18: Cooperative bargaining Chapter 19: Jean-Francois Mertens Chapter 20: M equilibrium Chapter 21: Berge equilibrium (II) Answering the public top questions about game theory. (III) Real world examples for the usage of game theory in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Game Theory.