示例#1
0
 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)
示例#2
0
 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