def putOnBoard(self, match, piece):
available_pos = match.board.unusedPositions()
fallback_i = random.randint(0, len(available_pos) - 1)
better_pos = available_pos[fallback_i]
alpha, beta = 0, Minimax.EVAL_WIN
if len(available_pos) >= Minimax.MINIMAX_1_UNTIL and \
self.max_depth > 1:
return Minimax(1).putOnBoard(match, piece)
if len(available_pos) >= Minimax.MINIMAX_2_UNTIL and \
self.max_depth > 2:
return Minimax(2).putOnBoard(match, piece)
if len(available_pos) >= Minimax.MINIMAX_3_UNTIL and \
self.max_depth > 3:
return Minimax(3).putOnBoard(match, piece)
for pos in available_pos:
eval = self.min_evaluation(
match.board, piece, pos,
alpha, beta, 1
)
if eval > alpha:
alpha = eval
better_pos = pos
ui.showPlayer(match.active_player)
ui.showSelectedPosition(better_pos)
return better_pos
def putOnBoard(self, match, piece):
available_pos = match.board.unusedPositions()
i = random.randint(0, len(available_pos) - 1)
ui.showPlayer(match.active_player)
ui.showSelectedPosition(available_pos[i])
return available_pos[i]
def putOnBoard(self, match, piece):
available_pos = match.board.unusedPositions()
if len(available_pos) >= 15:
return Random().putOnBoard(match, piece)
board_values = get_board_values(match.board.board)
better_color = maximize_property(
match.board.board,
{"propriety": "color", "value": piece.color},
board_values
)
better_height = maximize_property(
match.board.board,
{"propriety": "height", "value": piece.height},
board_values
)
better_shape = maximize_property(
match.board.board,
{"propriety": "shape", "value": piece.shape},
board_values
)
better_state = maximize_property(
match.board.board,
{"propriety": "state", "value": piece.state},
board_values
)
val_max = max((
better_color["value"],
better_height["value"],
better_shape["value"],
better_state["value"]
))
final_pos = None
for best in (better_color, better_height,
better_shape, better_state):
if best["value"] == val_max:
final_pos = best["position"]
if final_pos is None:
i = random.randint(0, len(available_pos) - 1)
final_pos = available_pos[i]
ui.showPlayer(match.active_player)
ui.showSelectedPosition(final_pos)
return final_pos
def selectPiece(self, match):
available_pieces = match.board.unusedPieces()
if len(available_pieces) < 1:
# trick for tournament, when board is full
return Piece({
"color": "blue",
"height": "small",
"shape": "round",
"state": "solid"
})
i = random.randint(0, len(available_pieces) - 1)
ui.showPlayer(match.active_player)
ui.showSelectedPiece(available_pieces[i])
return available_pieces[i]
def selectPiece(self, match):
available_pieces = match.board.unusedPieces()
if len(available_pieces) < 1:
# trick for tournament, when board is full
return Piece({
"color": "blue", "height": "small",
"shape": "round", "state": "solid"
})
available_pos = match.board.unusedPositions()
fallback_i = random.randint(0, len(available_pieces) - 1)
chosen_piece = available_pieces[fallback_i]
alpha, beta = 0, Minimax.EVAL_WIN
if len(available_pieces) >= Minimax.MINIMAX_1_UNTIL and \
self.max_depth > 1:
return Minimax(1).selectPiece(match)
if len(available_pieces) >= Minimax.MINIMAX_2_UNTIL and \
self.max_depth > 2:
return Minimax(2).selectPiece(match)
if len(available_pieces) >= Minimax.MINIMAX_3_UNTIL and \
self.max_depth > 3:
return Minimax(3).selectPiece(match)
for piece in available_pieces:
alpha = 0
for pos in available_pos:
eval = self.min_evaluation(
match.board, piece, pos,
alpha, beta, 1
)
alpha = max(alpha, eval)
if alpha < beta:
beta = alpha
chosen_piece = piece
ui.showPlayer(match.active_player)
ui.showSelectedPiece(chosen_piece)
return chosen_piece
def putOnBoard(self, match, piece):
ui.showPlayer(match.active_player)
return ui.askPosition(match.board.unusedPositions())
def selectPiece(self, match):
ui.showPlayer(match.active_player)
return ui.askSelectPiece(match.board.unusedPieces())