def calculate_best_score(self, game_state: GameState, action):
# pacman
next_game_state = game_state.getPacmanNextState(action)
next_pacman_position = next_game_state.getPacmanPosition()
# ghost
# next_ghost_position = tuple(map(lambda v: int(v), next_game_state.getGhostPosition(1)))
# print('\nnext Ghost position = ', next_ghost_position)
next_ghost_positions = next_game_state.getGhostPositions()
next_food_layout = next_game_state.getFood()
food_points = ReflexAgent.eaten_food_points if next_game_state.getNumFood() < game_state.getNumFood() else 0
ghost_penalization = ReflexAgent.ghost_penalization if self.pacman_will_die(next_pacman_position,
next_ghost_positions) else 0
scores = []
for x in range(next_food_layout.width):
for y in range(next_food_layout.height):
if self.has_food(next_food_layout, x, y):
pacman_distance_to_food = self.calculate_food_distance(game_state,
pacman_position=next_pacman_position,
food_position=(x, y))
distance_points = ReflexAgent.distance_coefficient / pacman_distance_to_food
score = distance_points + food_points - ghost_penalization
scores.append({'distance': pacman_distance_to_food, 'score': score,
'foodAt': [x, y], 'action': action})
if len(scores) == 0:
score = ReflexAgent.all_food_eaten_points - ghost_penalization
scores.append({'distance': 0, 'score': score, 'foodAt': None})
# best score first
scores.sort(key=lambda s: s['score'], reverse=True)
# get the best score
return scores[0]
