random¶
Generate random NormalFormGame instances.
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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.
Returns: - 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.
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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.
Returns: - g : NormalFormGame
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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.
Returns: - action_profile : tuple(ndarray(float, ndim=1))
Tuple of mixed_actions, one for each player.
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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.
Returns: - action_profile : Tuple(int)
Tuple of actions, one for each player.