## Abstract

The perfect folk theorem (Fudenberg and Maskin [1986]) need not rely on excessively complex strategies. We recover the perfect folk theorem for two person repeated games with discounting through neural networks (Hopfield [1982]) that have finitely many associative units. For any individually rational payoff vector, we need neural networks with at most 7 associative units, each of which can handle only elementary calculations such as maximum, minimum or threshold operation. The uniform upper bound of the complexity of equilibrium strategies differentiates this paer from Ben-Porath and Peleg [1987] in which we need to admit ever more complex strategies in order to expand the set of equilibrium outcomes.

Original language | English (US) |
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Pages (from-to) | 935-957 |

Number of pages | 23 |

Journal | Economic Theory |

Volume | 4 |

Issue number | 6 |

DOIs | |

State | Published - Nov 1994 |

## Keywords

- Repeated games with discounting
- bounded rationality
- folk theorem
- neural network
- target strategy

## ASJC Scopus subject areas

- Economics and Econometrics