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| class Game: | |
| def __init__(self, max_game=10000): | |
| self.p1 = Player('Alasdair') | |
| self.p2 = Player('Calum') | |
| self.max_game = max_game | |
| def winner(self, a1, a2): | |
| result = RPS.utilities.loc[a1, a2] | |
| if result == 1: return self.p1 | |
| elif result == -1: return self.p2 | |
| else: return 'Draw' | |
| def play(self, avg_regret_matching=False): | |
| def play_regret_matching(): | |
| for i in xrange(0, self.max_game): | |
| self.p1.update_strategy() | |
| self.p2.update_strategy() | |
| a1 = self.p1.action() | |
| a2 = self.p2.action() | |
| self.p1.regret(a1, a2) | |
| self.p2.regret(a2, a1) | |
| winner = self.winner(a1, a2) | |
| num_wins[winner] += 1 | |
| def play_avg_regret_matching(): | |
| for i in xrange(0, self.max_game): | |
| a1 = self.p1.action(use_avg=True) | |
| a2 = self.p2.action(use_avg=True) | |
| winner = self.winner(a1, a2) | |
| num_wins[winner] += 1 | |
| num_wins = { | |
| self.p1: 0, | |
| self.p2: 0, | |
| 'Draw': 0 | |
| } | |
| play_regret_matching() if not avg_regret_matching else play_avg_regret_matching() | |
| print num_wins | |
| def conclude(self): | |
| """ | |
| let two players conclude the average strategy from the previous strategy stats | |
| """ | |
| self.p1.learn_avg_strategy() | |
| self.p2.learn_avg_strategy() |
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