def test_compute_game_value_with_evaluation_function(self):
# We only check it runs
tic_tac_toe = pyspiel.load_game("tic_tac_toe")
game_score, _ = minimax.alpha_beta_search(tic_tac_toe,
value_function=lambda x: 0,
maximum_depth=1)
self.assertEqual(0., game_score)
def test_win(self):
tic_tac_toe = pyspiel.load_game("tic_tac_toe")
state = tic_tac_toe.new_initial_state()
# Construct:
# .o.
# .x.
# ...
state.apply_action(4)
state.apply_action(1)
game_score, _ = minimax.alpha_beta_search(tic_tac_toe, state=state)
self.assertEqual(1., game_score)
def test_loss(self):
tic_tac_toe = pyspiel.load_game("tic_tac_toe")
state = tic_tac_toe.new_initial_state()
# Construct:
# ...
# xox
# ..o
state.apply_action(5)
state.apply_action(4)
state.apply_action(3)
state.apply_action(8)
game_score, _ = minimax.alpha_beta_search(tic_tac_toe, state=state)
self.assertEqual(-1., game_score)
def step(self, state): _, action = minimax.alpha_beta_search(self._game, state=state) return action
def test_compute_game_value(self):
tic_tac_toe = pyspiel.load_game("tic_tac_toe")
game_score, _ = minimax.alpha_beta_search(tic_tac_toe)
self.assertEqual(0., game_score)
def play(self, state):
legal_actions = state.legal_actions()
_ , action = alpha_beta_search(state.get_game(), state, self.evaluate, 2 , self.idx)
return action