# random¶

Generate random NormalFormGame instances.

quantecon.game_theory.random.covariance_game(nums_actions, rho, random_state=None)[source]

Return a random NormalFormGame instance where the payoff profiles are drawn independently from the standard multi-normal with the covariance of any pair of payoffs equal to rho, as studied in [1].

Parameters: nums_actions : tuple(int) Tuple of the numbers of actions, one for each player. rho : scalar(float) Covariance of a pair of payoff values. Must be in [-1/(N-1), 1], where N is the number of players. random_state : int or np.random.RandomState, optional Random seed (integer) or np.random.RandomState instance to set the initial state of the random number generator for reproducibility. If None, a randomly initialized RandomState is used. g : NormalFormGame

References

 [1] Y. Rinott and M. Scarsini, “On the Number of Pure Strategy Nash Equilibria in Random Games,” Games and Economic Behavior (2000), 274-293.
quantecon.game_theory.random.random_game(nums_actions, random_state=None)[source]

Return a random NormalFormGame instance where the payoffs are drawn independently from the uniform distribution on [0, 1).

Parameters: nums_actions : tuple(int) Tuple of the numbers of actions, one for each player. random_state : int or np.random.RandomState, optional Random seed (integer) or np.random.RandomState instance to set the initial state of the random number generator for reproducibility. If None, a randomly initialized RandomState is used. g : NormalFormGame
quantecon.game_theory.random.random_mixed_actions(nums_actions, random_state=None)[source]

Return a tuple of random mixed actions (vectors of floats).

Parameters: nums_actions : tuple(int) Tuple of the numbers of actions, one for each player. random_state : int or np.random.RandomState, optional Random seed (integer) or np.random.RandomState instance to set the initial state of the random number generator for reproducibility. If None, a randomly initialized RandomState is used. action_profile : tuple(ndarray(float, ndim=1)) Tuple of mixed_actions, one for each player.
quantecon.game_theory.random.random_pure_actions(nums_actions, random_state=None)[source]

Return a tuple of random pure actions (integers).

Parameters: nums_actions : tuple(int) Tuple of the numbers of actions, one for each player. random_state : int or np.random.RandomState, optional Random seed (integer) or np.random.RandomState instance to set the initial state of the random number generator for reproducibility. If None, a randomly initialized RandomState is used. action_profile : Tuple(int) Tuple of actions, one for each player.