repeated_game¶
Tools for repeated game.

class
quantecon.game_theory.repeated_game.
RepeatedGame
(stage_game, delta)[source]¶ Bases:
object
Class representing an Nplayer repeated game.
Parameters:  stage_game : NormalFormGame
The stage game used to create the repeated game.
 delta : scalar(float)
The common discount rate at which all players discount the future.
Attributes:  sg : NormalFormGame
The stage game. See Parameters.
 delta : scalar(float)
See Parameters.
 N : scalar(int)
The number of players.
 nums_actions : tuple(int)
Tuple of the numbers of actions, one for each player.
Methods
equilibrium_payoffs
([method, options])Compute the set of payoff pairs of all purestrategy subgameperfect equilibria with public randomization for any repeated twoplayer games with perfect monitoring and discounting. 
equilibrium_payoffs
(method=None, options=None)[source]¶ Compute the set of payoff pairs of all purestrategy subgameperfect equilibria with public randomization for any repeated twoplayer games with perfect monitoring and discounting.
Parameters:  method : str, optional
The method for solving the equilibrium payoff set.
 options : dict, optional
A dictionary of method options. For example, ‘abreu_sannikov’ method accepts the following options:
 tol : scalar(float)
Tolerance for convergence checking.
 max_iter : scalar(int)
Maximum number of iterations.
 u_init : ndarray(float, ndim=1)
The initial guess of threat points.
Notes
Here lists all the implemented methods. The default method is ‘abreu_sannikov’.
 ‘abreu_sannikov’