Learning to Play Approximate Nash Equilibria in Games with Many Players

Arbeitspapier

We illustrate one way in which a population of boundedly rational individuals can learn to play an approximate Nash equilibrium. Players are assumed to make strategy choices using a combination of imitation and innovation. We begin by looking at an imitation dynamic and provide conditions under which play evolves to an imitation equilibrium; convergence is conditional on the network of social interaction. We then illustrate, through example, how imitation and innovation can complement each other; in particular, we demonstrate how imitation can .help. a population to learn to play a Nash equilibrium where more rational methods do not. This leads to our main result in which we provide a general class of large game for which the imitation with innovation dynamic almost surely converges to an approximate Nash, imitation equilibrium.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Nota di Lavoro ; No. 85.2004

Classification and Topics

• Classification: Wirtschaft ; Game Theory and Bargaining Theory: General ; Noncooperative Games ; Stochastic and Dynamic Games; Evolutionary Games; Repeated Games
• Subject: Imitation ; Best replay ; Convergence ; Nash equilibrium ; Verhaltensökonomik ; Begrenzte Rationalität ; Nash-Gleichgewicht ; Theorie ; Wiederholte Spiele

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Cartwright, Edward
• Event: Veröffentlichung
• (who): Fondazione Eni Enrico Mattei (FEEM)
• (where): Milano
• (when): 2004

Further information

• Handle: http://hdl.handle.net/10419/117957
• Last update: 10.03.2025, 11:41 AM CET