def compute_heuristic_score(victory_cell, cell, you):
p1_score = 0
p2_score = 0
p1_cell = 0
p2_cell = 0
empty_cell = 0
my_victory_cell = 0
opp_victory_cell = 0
my_corner = 0
new_board = Board()
board_scores = [[120, -20, 20, 5, 5, 20, -20, 120],
[-20, -40, -5, -5, -5, -5, -40, -20],
[20, -5, 15, 3, 3, 15, -5, 20], [5, -5, 3, 3, 3, 3, -5, 5],
[5, -5, 3, 3, 3, 3, -5, 5], [20, -5, 15, 3, 3, 15, -5, 20],
[-20, -40, -5, -5, -5, -5, -40, -20],
[120, -20, 20, 5, 5, 20, -20, 120]]
for i in [0, 7]:
for j in [0, 7]:
if cell[i][j] == you:
my_corner += 1
for i in victory_cell:
c = new_board.getColumnId(i[0])
r = new_board.getRowId(i[1])
if cell[r][c] == you:
my_victory_cell += 1
elif cell[r][c] != 'E':
opp_victory_cell += 1
if (opp_victory_cell >= 3 and my_victory_cell == 0) or (my_victory_cell == 0 and my_corner > 0) or \
(my_victory_cell == 4 and my_corner >= 2):
for i in victory_cell:
c = new_board.getColumnId(i[0])
r = new_board.getRowId(i[1])
if board_scores[r][c] <= 0:
board_scores[r][c] += 20
else:
board_scores[r][c] += 60
for r in range(8):
for c in range(8):
if cell[r][c] == you:
p1_cell += 1
p1_score += board_scores[r][c]
elif cell[r][c] != 'E':
p2_cell += 1
p2_score += board_scores[r][c]
else:
empty_cell += 1
if empty_cell > 0:
return p1_score - p2_score
else:
return p1_cell - p2_cell
def minimax_max(victory_cell, cell, you, depth):
possible_positions = []
if type(cell) is tuple:
new_board = Board()
for i in range(8):
for j in range(8):
new_board.data[i][j] = cell[i][j]
for (r, c) in itertools.product(list('12345678'), list('abcdefgh')):
if new_board.isPlaceable(c + r, you):
possible_positions.append(c + r)
move_states = {
move: play_move(new_board, you, new_board.getColumnId(move[0]),
new_board.getRowId(move[1]))
for move in possible_positions
}
else:
for (r, c) in itertools.product(list('12345678'), list('abcdefgh')):
if cell.isPlaceable(c + r, you):
possible_positions.append(c + r)
move_states = {
move: play_move(cell, you, cell.getColumnId(move[0]),
cell.getRowId(move[1]))
for move in possible_positions
}
best_move = None
best_value = None
if len(possible_positions) > 0:
if depth == 1:
for move, state in move_states.items():
if best_move == None or minimax_min(victory_cell, state, you,
depth + 1) > best_value:
best_move = move
best_value = minimax_min(victory_cell, state, you,
depth + 1)
return best_move
else:
for move, state in move_states.items():
if best_move == None or minimax_min(victory_cell, state, you,
depth + 1) > best_value:
best_value = minimax_min(victory_cell, state, you,
depth + 1)
return best_value
return compute_heuristic_score(victory_cell, cell, you)
def test_getRowId(self):
x = Board()
y = ['1', '2', '3', '4', '5', '6', '7', '8']
for i in range(8):
self.assertEqual(x.getRowId(y[i]), i)