repeated_game

Tools for repeated game.

class quantecon.game_theory.repeated_game.RepeatedGame(stage_game, delta)[source]

Bases: object

Class representing an N-player repeated game.

Parameters:
stage_gameNormalFormGame

The stage game used to create the repeated game.

deltascalar(float)

The common discount rate at which all players discount the future.

Attributes:
sgNormalFormGame

The stage game. See Parameters.

deltascalar(float)

See Parameters.

Nscalar(int)

The number of players.

nums_actionstuple(int)

Tuple of the numbers of actions, one for each player.

Methods

equilibrium_payoffs([method, options])

Compute the set of payoff pairs of all pure-strategy subgame-perfect equilibria with public randomization for any repeated two-player games with perfect monitoring and discounting.

equilibrium_payoffs(method=None, options=None)[source]

Compute the set of payoff pairs of all pure-strategy subgame-perfect equilibria with public randomization for any repeated two-player games with perfect monitoring and discounting.

Parameters:
methodstr, optional

The method for solving the equilibrium payoff set.

optionsdict, optional

A dictionary of method options. For example, ‘abreu_sannikov’ method accepts the following options:

tolscalar(float)

Tolerance for convergence checking.

max_iterscalar(int)

Maximum number of iterations.

u_initndarray(float, ndim=1)

The initial guess of threat points.

Notes

Here lists all the implemented methods. The default method is ‘abreu_sannikov’.

  1. ‘abreu_sannikov’