Game learning theory

Author: (USA) Fudenberg, (USA) Levine, translated by Xiao Zhengyan, Hou Chengqi
Publisher:
Publish Date: 2004-07-01
Features: This book collects the main existing achievements in the forefront of learning and evolutionary game theory, as well as the new contributions from two authoritative scholars in the field. For anyone engaged in learning theory, evolutionary game theory research, or the application of evolutionary game theory in research, this book will be indispensable. Written by two distinguished scholars who have made outstanding contributions to the fields of evolutionary and learning in economic theory and game theory, this excellent work covers a very broad scope. It will be highly useful for advanced undergraduates, graduate students, and theoretical researchers. The book skillfully introduces a large number of models proposed in recent years in learning and evolutionary game theory, provides very detailed explanations for these models with examples, and connects them together. In economics, the vast majority of non-cooperative game theory focuses on equilibrium issues in games, particularly Nash equilibrium and its refinements. The traditional explanation for when and why equilibria arise is that they are the result of players' analysis and introspection under the assumption that the rules of the game, players' rationality, and players' payoff functions are common knowledge. This theory faces many conceptual and empirical problems. In the book Learning in Games, Jean Fudenberg and David K. Levine propose an alternative explanation: equilibria are the long-term outcomes of non-completely rational players seeking to optimize this process over time. The models they study provide a foundation for equilibrium theory and offer useful methods for economists to evaluate and improve traditional equilibrium concepts.