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Learning in games with bounded memory

Version 2 2024-06-18, 01:38
Version 1 2017-07-27, 11:42
journal contribution
posted on 2006-01-01, 00:00 authored by Jaideep Roy
The paper studies infinite repetition of finite strategic form games. Players use a backward looking learning behavior and face bounds on their cognitive capacities. We show that for any given belief-probability over the set of possible outcomes where players have no experience, games can be payoff classified and there always exists a stationary state in the space of action profiles. In particular, if the belief-probability assumes all possible outcomes without experience to be equally likely, in one class of Prisoners' Dilemmas where the uniformly weighted average defecting payoff is higher than the cooperative payoff and the uniformly weighted average cooperative payoff is lower than the defecting payoff, play converges in the long run to the static Nash equilibrium while in the other class of Prisoners' Dilemmas where the reverse holds, play converges to cooperation. Results are applied to a large class of 2 × 2 games.

History

Journal

Control and cybernetics

Volume

35

Issue

2

Article number

5

Pagination

303 - 333

Publisher

Systems Research Institute of the Polish Academy of Sciences

ISSN

0324-8569

Publication classification

CN.1 Other journal article