def _initialize_game_state(self): effective_payoff_size = self._game_num_players self._meta_games = [ np.array(utils.empty_list_generator(effective_payoff_size)) for _ in range(effective_payoff_size) ] self.update_empirical_gamestate(seed=None)
def _initialize_game_state(self): effective_payoff_size = self._game_num_players self._meta_games = [ np.array(utils.empty_list_generator(effective_payoff_size)) for _ in range(effective_payoff_size) ] super(PSROQuiesceSolver, self).update_empirical_gamestate(seed=None) self.update_complete_ind([0 for _ in range(self._game_num_players)], add_sample=True) self.number_profile_sampled = 1