def combined_full(game, player):
if game.move_count < 10:
return distance_to_center(game, player)
if game.move_count < 20:
return improved_score(game, player)
# if above 20:
return improved_score(game, player) + diff_density(game, player)
def combined_improved_density_at_end(game, player):
"""
Simple evaluation function that combine improved-score heuristic and density function heuristic
"""
if game.move_count < 20:
# At the beginning we need to go fast
score = improved_score(game, player)
else:
# At the end of a game/middle of a game we need a more precise heuristic that could take a bit more of time
score = improved_score(game, player) + diff_density(game, player)
return float(score)
def custom_score(game, player):
"""Calculate the heuristic value of a game state from the point of view
of the given player.
Note: this function should be called from within a Player instance as
`self.score()` -- you should not need to call this function directly.
Parameters
----------
game : `isolation.Board`
An instance of `isolation.Board` encoding the current state of the
game (e.g., player locations and blocked cells).
player : object
A player instance in the current game (i.e., an object corresponding to
one of the player objects `game.__player_1__` or `game.__player_2__`.)
Returns
-------
float
The heuristic value of the current game state to the specified player.
"""
# TODO: finish this function!
return improved_score(game, player)
def heuristic_main_alt_less_more(game, player):
"""
weight number of moves more highly at the beginning of the game, then amount of open space
near end game (when improved score gives a winner or loser, prop won't have an effect due to the infinities)
"""
prop = len(game.get_blank_spaces()) / total_board_spaces
return prop * improved_score(game, player) + heuristic2(game, player)
def weighted_improved_score(game, player):
"""This metric is comparable to the improved score, but it will divide this outcome by the number of
blank spaces. For instance, if there are only 3 blank spaces, 2 possible moves is pretty good. 2 possible
moves if there are 20 blank spaces is not as good.
Parameters
----------
game : `isolation.Board`
An instance of `isolation.Board` encoding the current state of the
game (e.g., player locations and blocked cells).
player : object
A player instance in the current game (i.e., an object corresponding to
one of the player objects `game.__player_1__` or `game.__player_2__`.)
Returns
-------
float
The heuristic value of the current game state to the specified player.
"""
if game.is_loser(player):
return float("-inf")
if game.is_winner(player):
return float("inf")
improved = improved_score(game, player)
available_spaces = len(game.get_blank_spaces())
return improved / available_spaces
def improved_with_sleep(game, player):
"""
return opposite of improved_score, so we help the opponnent
:param game:
:param player:
:return:
"""
res = -improved_score(game, player)
time.sleep(0.01) # just to make sure we timeout a lot
return float(res)
def test6():
player1 = AlphaBetaPlayer(search_depth=1, score_fn=custom_score)
player2 = AlphaBetaPlayer(search_depth=1, score_fn=custom_score_3)
game = isolation.Board(player1, player2, height=5, width=5)
game.apply_move((0, 3))
print(game.to_string())
game.apply_move((4, 4))
print(game.to_string())
game.apply_move((3, 2))
print(game.to_string())
game.apply_move((1, 1))
game.apply_move((2, 0))
game.apply_move((3, 0))
game.apply_move((1, 2))
print(game.to_string())
print(custom_score(game, game.active_player))
print(custom_score(game, game.inactive_player))
print(custom_score_2(game, game.active_player))
print(custom_score_2(game, game.inactive_player))
print(custom_score_3(game, game.active_player))
print(custom_score_3(game, game.inactive_player))
print(improved_score(game, game.active_player))
print(improved_score(game, game.inactive_player))
def agrressive_first_then_preserving(game, player):
"""
fonctionne pas trop mal
:param game:
:param player:
:return:
"""
if game.is_loser(player):
return float("-inf")
if game.is_winner(player):
return float("inf")
total_space = game.width * game.height
game_duration = len(game.get_blank_spaces()) / float(total_space)
if game_duration <= 0.25:
# aggressif en debut de partie..
return improved_agressive(game, player)
else:
return improved_score(game, player)
def combined_improved_and_density(game, player):
return improved_score(game, player) + diff_density(game, player)