def setUp(self):
reload(game_agent)
self.player1 = game_agent.MinimaxPlayer(2,
sample_players.improved_score)
self.player2 = sample_players.GreedyPlayer()
self.game = isolation.Board(self.player1, self.player2, 9, 9)
self.time_left = lambda: float("inf")
def test_minimax(self):
self.minimax_player = game_agent.MinimaxPlayer(
score_fn=sample_players.center_score, timeout=float("inf"))
self.greedy_player = sample_players.GreedyPlayer()
self.game = isolation.Board(self.minimax_player, self.greedy_player)
# self.game.play(time_limit=float("inf"))
self.minimax_player.match_boards(self.game, self.game)
def test_single_min_max(self):
width, height = 7, 7
#timeout = float("-inf")
timeout = 10.
self.player1 = game_agent.MinimaxPlayer(
search_depth=3, score_fn=game_agent.custom_score, timeout=timeout)
self.player2 = sample_players.GreedyPlayer(
score_fn=game_agent.custom_score_3)
self.game = isolation.Board(self.player1,
self.player2,
width=width,
height=height)
#self.game.apply_move((random.randint(0, self.game.width-1), random.randint(0, self.game.height-1)))
#self.game.apply_move((random.randint(0, self.game.width-1), random.randint(0, self.game.height-1)))
print(self.game.to_string())
# players take turns moving on the board, so player1 should be next to move
assert (self.player1 == self.game.active_player)
# get a list of the legal moves available to the active player
print(self.game.get_legal_moves())
# play the remainder of the game automatically -- outcome can be "illegal
# move", "timeout", or "forfeit"
winner, history, outcome = self.game.play()
print("\nWinner: {}\nOutcome: {}".format(
"player 1" if winner == self.player1 else "player 2", outcome))
print("\nstate:\n{}".format(self.game.to_string()))
print("\nhistory:\n{}".format(history))
def setUp(self):
reload(game_agent)
self.player1 = game_agent.MinimaxPlayer()
self.player2 = sample_players.GreedyPlayer(
sample_players.improved_score)
self.player3 = game_agent.AlphaBetaPlayer()
# self.game = isolation.Board(self.player1, self.player2,7,7)
self.game = isolation.Board(self.player3, self.player2, 7, 7)
def setUp(self):
self.player1 = game_agent.MinimaxPlayer(score_fn=self.custom_score,
search_depth=3)
self.player2 = sample_players.GreedyPlayer()
self.game = isolation.Board(self.player1, self.player2)
minmax_value = self.player1.get_move(self.game, lambda: 10000)
print(minmax_value)
def setUp(self):
reload(game_agent)
self.player1 = game_agent.MinimaxPlayer()
self.player2 = sample_players.GreedyPlayer()
self.player3 = sample_players.RandomPlayer()
self.player4 = game_agent.AlphaBetaPlayer()
self.player5 = game_agent.AlphaBetaPlayer()
self.player6 = game_agent.MinimaxPlayer()
self.game = None
def test_score_time(self):
player1 = game_agent.MinimaxPlayer()
player2 = sample_players.GreedyPlayer()
game = isolation.Board(player1, player2)
for _ in range(0, 2):
game.apply_move(random.choice(game.get_legal_moves()))
game_agent.custom_score(game, game.get_player_location(game.active_player))
game_agent.custom_score_2(game, game.get_player_location(game.active_player))
game_agent.custom_score_3(game, game.get_player_location(game.active_player))
def reset_boards(self):
self.my_player = game_agent.MinimaxPlayer(3,game_agent.custom_score,10)
self.opponent = sample_players.GreedyPlayer(sample_players.open_move_score)
self.game_board_1 = TestBoard(self.my_player, self.opponent)
self.game_board_2 = TestBoard(self.opponent,self.my_player)
self.my_player = game_agent.MinimaxPlayer(5,game_agent.custom_score,10)
self.game_board_3 = TestBoard(self.my_player, self.opponent)
self.my_player = game_agent.MinimaxPlayer(10,game_agent.custom_score,10)
self.game_board_4 = TestBoard(self.my_player, self.opponent)
self.my_player = game_agent.MinimaxPlayer(3,game_agent.custom_score_2,10)
self.game_board_5 = TestBoard(self.my_player, self.opponent)
self.my_player = game_agent.MinimaxPlayer(3,game_agent.custom_score_3,10)
self.game_board_6 = TestBoard(self.my_player, self.opponent)
def test_alpha_beta(self):
"""Test Alfa beta agains GreedPlayer"""
player1 = game_agent.AlphaBetaPlayer()
player2 = sample_players.GreedyPlayer()
game = isolation.Board(player1, player2, 3, 5)
winner, history, outcome = game.play()
self.assertNotEqual(outcome, 'timeout', "AlphaBeta should not lost by timeout")
game = isolation.Board(player1, player2)
winner, history, outcome = game.play()
self.assertNotEqual(outcome, 'timeout', "AlphaBeta should not lost by timeout")
def test_minimax_func(self):
minimax_player = game_agent.MinimaxPlayer(search_depth=1, score_fn=sample_players.improved_score)
other_player = sample_players.GreedyPlayer()
state = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 51, 43]
game = isolation.Board(minimax_player, other_player, width=9, height=9)
game._board_state = state
legal_moves = game.get_legal_moves()
move = minimax_player.get_move(game, lambda: 10)
print(game.to_string())
print('Available choices:')
print(legal_moves)
print(move)
assert(move in legal_moves)
def test_greedy_player(self):
"""Test against GreedPlayer"""
# create an isolation board (by default 7x7)
player1 = game_agent.MinimaxPlayer()
player2 = sample_players.GreedyPlayer()
game = isolation.Board(player1, player2, 3, 5)
winner, history, outcome = game.play()
self.assertNotEqual(outcome, 'forfeit', "MinimaxPlayer should not lost by forfeit")
self.assertNotEqual(outcome, 'timeout', "MinimaxPlayer should not lost by timeout")
game = isolation.Board(player1, player2)
winner, history, outcome = game.play()
self.assertNotEqual(outcome, 'forfeit', "MinimaxPlayer should not lost by forfeit")
self.assertNotEqual(outcome, 'timeout', "MinimaxPlayer should not lost by timeout")
def setUp(self):
reload(game_agent)
self.player1 = game_agent.MinimaxPlayer()
self.player2 = sample_players.GreedyPlayer()
self.game = isolation.Board(self.player1, self.player2)
def setUp(self):
reload(game_agent)
self.player1 = sample_players.GreedyPlayer()
self.player2 = game_agent.AlphaBetaPlayer(
score_fn=sample_players.open_move_score, timeout=20)
self.game = isolation.Board(self.player1, self.player2)