def test_random_vs_stateful(self):
game = pyspiel.load_game("tic_tac_toe")
bots = [
pyspiel.make_stateful_random_bot(game, 0, 1234),
uniform_random.UniformRandomBot(1, np.random.RandomState(4321))
]
for _ in range(1000):
evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
def test_can_play_single_player(self):
game = pyspiel.load_game("catch")
max_simulations = 100
evaluator = mcts.RandomRolloutEvaluator(n_rollouts=20)
bots = [mcts.MCTSBot(game, UCT_C, max_simulations, evaluator)]
v = evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
self.assertGreater(v[0], 0)
def test_can_play_both_sides(self):
game = pyspiel.load_game("tic_tac_toe")
bot = mcts.MCTSBot(game, UCT_C, max_simulations=100,
evaluator=mcts.RandomRolloutEvaluator(n_rollouts=20))
bots = [bot, bot]
v = evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
self.assertEqual(v[0] + v[1], 0)
def test_cpp_vs_python(self, bots):
results = np.array([
evaluate_bots.evaluate_bots(GAME.new_initial_state(), bots,
np.random) for _ in range(10000)
])
average_results = np.mean(results, axis=0)
np.testing.assert_allclose(average_results, [0.125, -0.125], atol=0.1)
def test_can_play_three_player_stochastic_games(self):
game = pyspiel.load_game("pig(players=3,winscore=20,horizon=30)")
max_simulations = 100
evaluator = mcts.RandomRolloutEvaluator(n_rollouts=5)
bots = [
mcts.MCTSBot(game, UCT_C, max_simulations, evaluator),
mcts.MCTSBot(game, UCT_C, max_simulations, evaluator),
mcts.MCTSBot(game, UCT_C, max_simulations, evaluator),
]
v = evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
self.assertEqual(sum(v), 0)
def test_cpp_vs_python(self):
game = pyspiel.load_game("kuhn_poker")
bots = [
pyspiel.make_uniform_random_bot(0, 1234),
uniform_random.UniformRandomBot(1, np.random.RandomState(4321))
]
results = np.array([
evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
for _ in range(10000)
])
average_results = np.mean(results, axis=0)
np.testing.assert_allclose(average_results, [0.125, -0.125], atol=0.1)
def test_can_play_tic_tac_toe(self):
game = pyspiel.load_game("tic_tac_toe")
uct_c = math.sqrt(2)
max_simulations = 100
evaluator = mcts.RandomRolloutEvaluator(n_rollouts=20)
bots = [
mcts.MCTSBot(game, 0, uct_c, max_simulations, evaluator),
mcts.MCTSBot(game, 1, uct_c, max_simulations, evaluator),
]
v = evaluate_bots.evaluate_bots(game.new_initial_state(), bots,
np.random)
self.assertEqual(v[0] + v[1], 0)
def test_can_play_three_player_game(self):
game = pyspiel.load_game("pig(players=3,winscore=20,horizon=30)")
uct_c = math.sqrt(2)
max_search_nodes = 100
evaluator = mcts.RandomRolloutEvaluator(n_rollouts=5)
bots = [
mcts.MCTSBot(game, 0, uct_c, max_search_nodes, evaluator),
mcts.MCTSBot(game, 1, uct_c, max_search_nodes, evaluator),
mcts.MCTSBot(game, 2, uct_c, max_search_nodes, evaluator),
]
v = evaluate_bots.evaluate_bots(game.new_initial_state(), bots,
np.random)
self.assertEqual(sum(v), 0)
def ismcts_play_game(self, game):
evaluator = pyspiel.RandomRolloutEvaluator(1, SEED)
for final_policy_type in [
pyspiel.ISMCTSFinalPolicyType.NORMALIZED_VISIT_COUNT,
pyspiel.ISMCTSFinalPolicyType.MAX_VISIT_COUNT,
pyspiel.ISMCTSFinalPolicyType.MAX_VALUE
]:
bot = pyspiel.ISMCTSBot(SEED, evaluator, 5.0, 1000, -1, final_policy_type,
False, False)
bots = [bot] * game.num_players()
evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
bot = pyspiel.ISMCTSBot(SEED, evaluator, 5.0, 1000, 10, final_policy_type,
False, False)
bots = [bot] * game.num_players()
evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
bot = pyspiel.ISMCTSBot(SEED, evaluator, 5.0, 1000, 10, final_policy_type,
True, True)
bots = [bot] * game.num_players()
evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
def xinxin_play_game(self, game):
bots = []
for _ in range(4):
bots.append(pyspiel.make_xinxin_bot(game.get_parameters()))
evaluate_bots.evaluate_bots(game.new_initial_state(), bots, np.random)
