English

Bounded Rationality, Strategy Simplification, and Equilibrium

Computer Science and Game Theory 2015-03-13 v3 Computational Complexity

Abstract

It is frequently suggested that predictions made by game theory could be improved by considering computational restrictions when modeling agents. Under the supposition that players in a game may desire to balance maximization of payoff with minimization of strategy complexity, Rubinstein and co-authors studied forms of Nash equilibrium where strategies are maximally simplified in that no strategy can be further simplified without sacrificing payoff. Inspired by this line of work, we introduce a notion of equilibrium whereby strategies are also maximally simplified, but with respect to a simplification procedure that is more careful in that a player will not simplify if the simplification incents other players to deviate. We study such equilibria in two-player machine games in which players choose finite automata that succinctly represent strategies for repeated games; in this context, we present techniques for establishing that an outcome is at equilibrium and present results on the structure of equilibria.

Keywords

Cite

@article{arxiv.1002.4577,
  title  = {Bounded Rationality, Strategy Simplification, and Equilibrium},
  author = {Hubie Chen},
  journal= {arXiv preprint arXiv:1002.4577},
  year   = {2015}
}
R2 v1 2026-06-21T14:50:45.076Z