def main():
board = HexBoard(2)
num_of_cells = board.get_board_size() * board.get_board_size()
for nc in range(int(num_of_cells / 2)):
## Just a small heuristic for opening strategy, you can test this if you want. But then you have to comment the move_blue below out too
# if board.size % 2 != 0 and len(board.get_move_list()) == len(board.get_all_vertices()): # If it's the first move and the board is uneven
# move_blue = (board.size // 2, board.size // 2) # Always place the first move in the middle
# else:
# move_blue = ab.alphabeta_move(board, depth=2, is_max=True)
move_blue = ab.alphabeta_move(board, depth=4, is_max=True)
#move_blue = ab.alphabeta_move_Id(board, is_max=True, show_AI=True)
board = ab._update_board(board, move_blue, is_max=True)
board.print()
if board.is_game_over(
): # TODO: add condition for game over without no winning (board full)
print("==== BLUE WINS ====")
board.print()
# break
return "blue"
move_red = ab.alphabeta_move(board, depth=2, is_max=True)
#move_red = ab.alphabeta_move_Id(board, is_max=True, show_AI=True)
board = ab._update_board(
board, move_red, is_max=False
) # Using false here and true for the alphabeta is a bit confusing, but we need it to make moves for red here.
board.print()
if board.is_game_over(
): # TODO: add condition for game over without no winning (board full)
print("==== RED WINS ====")
board.print()
# break
return "red"
def alphabeta_Id(board: HexBoard, depth: int, alpha: float, beta: float,
is_max: bool) -> float:
# board.print()
print("in alphabeta_Id000000000")
try:
(hit, g, ttbm) = transposition_table.lookup(board,
board.get_board_size(),
depth)
print("in alphabeta_Id", hit, g, ttbm)
except Exception as e: #
print('Exception in running lookup function: ' + str(e))
if hit():
return g
if depth == 0 or board.is_game_over():
g = dijkstra_eval(board)
bm = ()
legals = board.get_move_list()
if legals:
if is_max:
g: float = -_INF
for move in ttbm + legals:
updated_board: HexBoard = _update_board(
board, move, is_max) # y do we make the move first?
gc = alphabeta_Id(updated_board, depth - 1, alpha, beta,
is_max)
if gc > g:
bm = updated_board
g = gc
alpha = max(alpha, g)
if beta <= alpha:
break
else: # if is_max False
g: float = _INF
for move in ttbm + legals:
updated_board: HexBoard = _update_board(board, move, is_max)
gc = alphabeta_Id(updated_board, depth - 1, alpha, beta,
is_max)
if gc < g:
bm = updated_board
g = gc
beta = min(beta, g)
if beta <= alpha:
break
transposition_table.store(updated_board,
updated_board.get_board_size(), g, depth, bm)
return g
else:
print("NO MORE LEGAL MOVES LEFT")
return dijkstra_eval(board)
def dijkstra_eval(board: HexBoard):
"""
Checks the best path from every possible source (e.g. L to R for blue) and
then returns the best evaluation score of the board based on the most
efficient source
"""
best_eval_score = -np.inf
for i in range(board.get_board_size()):
blue_source = (0, i)
red_source = (i, 0)
blue_dists, _ = simple_dijkstra(board, blue_source, True)
red_dists, _ = simple_dijkstra(board, red_source, False)
blue_score = get_shortest_path(board, blue_dists, board.BLUE)
red_score = get_shortest_path(board, red_dists, board.RED)
eval_score = red_score - blue_score
if eval_score > best_eval_score:
best_eval_score = eval_score
return best_eval_score