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’.
‘abreu_sannikov’