Averaged predictions and the learning of equilibrium play
The main objects here are noncooperative games in which all externalities occur via a one-dimensional variable. So-called mean-value iterates are used to approach Nash equilibrium. The proposed schemes generalize many received methods, and can be interpreted as learning taking place during repeated play. An important feature is that no player need to be fully informed about the game structure. Particular examples include Cournot oligopolies and some nonatomic market games.
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References listed on IDEAS
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- Drew Fudenberg & David K. Levine, 1996.
"The Theory of Learning in Games,"
Levine's Working Paper Archive
624, David K. Levine.
- Smale, Steve, 1980. "The Prisoner's Dilemma and Dynamical Systems Associated to Non-Cooperative Games," Econometrica, Econometric Society, vol. 48(7), pages 1617-34, November.
- Gjerstad, Steven, 1996.
"The Rate of Convergence of Continuous Fictitious Play,"
Springer, vol. 7(1), pages 161-77, January.
- Steven Gjerstad, 1995. "The rate of convergence of continuous fictitious play," Economic Theory, Springer, vol. 7(1), pages 161-178.
- Thorlund-Petersen, Lars, 1990. "Iterative computation of cournot equilibrium," Games and Economic Behavior, Elsevier, vol. 2(1), pages 61-75, March.
- Young, H Peyton, 1993. "The Evolution of Conventions," Econometrica, Econometric Society, vol. 61(1), pages 57-84, January.
- Rath, Kali P, 1992. "A Direct Proof of the Existence of Pure Strategy Equilibria in Games with a Continuum of Players," Economic Theory, Springer, vol. 2(3), pages 427-33, July.
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