def utility(state: State, maximizing_player):
"""
utility and heuristic function
"""
best_move_score = -1
#######################[Goal]#########################
is_current_player_stuck = is_stuck(state, state.player_type)
other_player = RIVAL if state.player_type == PLAYER else PLAYER
# Check if stuck
if is_current_player_stuck:
if state.player_type == PLAYER:
state.players_score[state.player_type] -= state.penalty_score
else:
state.players_score[state.player_type] += state.penalty_score
return state.players_score[
state.player_type] - state.players_score[other_player]
######################################################
# Else
#--------------------------------------------------
################# Available Steps #################
#--------------------------------------------------
player_available_steps = availables(state.board, state.locations[PLAYER])
h1 = 4 - player_available_steps
h4 = player_available_steps
#--------------------------------------------------
################# Fruits Distance #################
#--------------------------------------------------
h2 = -1
if state.fruits_ttl > 0 and len(state.fruits_dict) > 0:
min_fruit_dist = float('inf')
for fruit_loc in state.fruits_dict:
curr_fruit_dist = Manhattan(state.locations[state.player_type],
fruit_loc)
# Check what is the closest fruit reachable
if curr_fruit_dist < min_fruit_dist and curr_fruit_dist <= state.fruits_ttl:
other_player_fruit_dist = Manhattan(
state.locations[other_player], fruit_loc)
if curr_fruit_dist < other_player_fruit_dist:
min_fruit_dist = curr_fruit_dist
max_dist = len(state.board) + len(state.board[0])
h2 = (max_dist * 10.0 /
min_fruit_dist) + 1 if min_fruit_dist < float('inf') else -1
#--------------------------------------------------
################# Reachable Squrs #################
#--------------------------------------------------
reachables_player = reachables(state.board, state.locations[PLAYER])
reachables_rival = reachables(state.board, state.locations[RIVAL])
h3 = reachables_player - reachables_rival # We want more for us
#--------------------------------------------------
################# Combine it all. #################
#--------------------------------------------------
if not state.half_game():
w = 0.8 if h2 > 0 else 1
best_move_score = w * (h1 - h3) + (1 - w) * h2
else:
w = 0.7 if h2 > 0 else 1
best_move_score = w * (h4 + h3) + (1 - w) * h2
best_move_score += state.players_score[state.player_type]
return best_move_score
def make_move(self, time_limit, players_score):
"""Make move with this Player.
input:
- time_limit: float, time limit for a single turn.
output:
- direction: tuple, specifing the Player's movement, chosen from self.directions
"""
start_time = time.time()
d = 1
reach_the_end = False
best_direction = None
chosen_state = None
time_limit = (2 * self.game_time *
float(self.player_turns - self.turns + 1)) / (
(self.player_turns + 1) * self.player_turns)
time_limit += self.spaire_time
if time_limit >= 5:
TIME_ESTIMATION = 0.9
else:
TIME_ESTIMATION = 0.85
#print(f'Time limit: {time_limit}')
while not reach_the_end: # and d < len(state.board)*len(state.board[0]):
iter_time_limit = TIME_ESTIMATION * (time_limit -
(time.time() - start_time))
#print(f'>>>Iter time: {iter_time_limit}')
state = State(get_directions(), self.board, self.locations,
self.fruits_on_board_dict, PLAYER, players_score,
self.penalty_score, self.fruits_ttl, self.turns)
try:
_, best_direction, reach_the_end, chosen_state = self.alphabeta.search(
state,
d,
True,
iter_time_limit,
alpha=float('-inf'),
beta=float('inf'))
d += 1
except Exception as e:
self.spaire_time = time_limit - (time.time() - start_time)
break
# Set new location
if best_direction == None:
best_direction = self.get_random_move()
self.set_player_location(best_direction)
self.turns += 1
return best_direction
def make_move(self, time_limit, players_score):
"""Make move with this Player.
input:
- time_limit: float, time limit for a single turn.
output:
- direction: tuple, specifing the Player's movement, chosen from self.directions
"""
start_time = time.time()
d = 1
# Make the initial state:
reach_the_end = False
best_direction = None
chosen_state = None
if time_limit >= 5:
TIME_ESTIMATION = 0.9
else:
TIME_ESTIMATION = 0.85
while not reach_the_end:
iter_time_limit = TIME_ESTIMATION * (time_limit -
(time.time() - start_time))
state = State(get_directions(), self.board, self.locations,
self.fruits_on_board_dict, PLAYER, players_score,
self.penalty_score, self.fruits_ttl, self.turns)
try:
_, best_direction, reach_the_end, chosen_state = self.minimax.search(
state, d, True, iter_time_limit)
d += 1
except Exception as e:
break
# Set new location
if best_direction == None:
best_direction = self.get_random_move()
self.set_player_location(best_direction)
self.turns += 1
return best_direction
def make_move(self, time_limit, players_score):
"""Make move with this Player.
input:
- time_limit: float, time limit for a single turn.
output:
- direction: tuple, specifing the Player's movement, chosen from self.directions
"""
d = 2
reach_the_end = False
best_direction = None
chosen_state = None
time_limit = float('inf')
while not reach_the_end: # and d < len(state.board)*len(state.board[0]):
state = State(get_directions(), self.board, self.locations,
self.fruits_on_board_dict, PLAYER, players_score,
self.penalty_score, self.fruits_ttl, self.turns)
try:
_, best_direction, reach_the_end, chosen_state = self.alphabeta.search(
state,
d,
True,
time_limit,
alpha=float('-inf'),
beta=float('inf'))
break
#d += 1
except Exception as e:
break
# Set new location
if best_direction == None:
best_direction = self.get_random_move()
self.set_player_location(best_direction)
self.turns += 1
return best_direction