def minimax(victory_cell, cur_state, you, depth, isMax, alpha, beta):
game = Board()
game.update(cur_state)
color = 'W' if you == "BLACK" else 'B'
final = evaluated(victory_cell, game, color)
if final == you:
return 9999
elif final != 'DRAW' and final != None:
return -9999
elif final == 'DRAW':
return 0
if depth == 0 and game.isPlayable(color):
if isMax:
return heuristic(victory_cell, game, you, True)
else:
return heuristic(victory_cell, game, you, False)
if isMovesLeft(game, color) == False:
return 0
if isMax:
best = -9999
for (x, y) in itertools.product(list('12345678'), list('abcdefgh')):
if game.isPlaceable(y + x, color):
new_game = Board()
new_game.update(cur_state)
new_game.place(y + x, color)
new_state = new_game.getCellLineList()
best = max(
best,
minimax(victory_cell, new_state, you, depth - 1, False,
alpha, beta))
alpha = max(alpha, best)
if beta <= alpha:
break
# print('max:', best)
return best
else:
best = 9999
for (x, y) in itertools.product(list('12345678'), list('abcdefgh')):
if game.isPlaceable(y + x, color):
new_game = Board()
new_game.update(cur_state)
new_game.place(y + x, color)
new_state = new_game.getCellLineList()
best = min(
best,
minimax(victory_cell, new_state, you, depth - 1, True,
alpha, beta))
beta = min(beta, best)
if beta <= alpha:
break
# print('min:', best)
return best
def findBestMove(state, depth):
global best
global color
global victory_cells
game = Board()
game.update(state)
bestMoveVal = -999999
listPosiblePositions = posiblePositions(game, color)
bestStep = listPosiblePositions[0]
for step in listPosiblePositions:
global best
best = 0
# create new game
newGame = Board()
newGame.update(state)
newGame.place(step, color)
# get state
newState = newGame.getCellLineList()
# get score of move
moveVal = minimax(newState, depth, -999999, 999999, True)
# update step
if (moveVal > bestMoveVal):
bestMoveVal = moveVal
bestStep = step
print('step:', bestStep)
return bestStep
def minBot(victory_cell, cell_line, you, alpha, beta, depth):
cell = Board()
cell.update(cell_line)
color = 'W' if you == "BLACK" else 'B'
result = is_end(victory_cell, cell, color)
if depth == 0 or result != None and result != you:
return Heuristic(victory_cell, cell, color, False)
# elif result != None and result != you:
# return 999998, None, None
elif result == you:
return -999998, None, None
minv = 999999
px = None
py = None
cur_weight = getWeightSquares(cell, color)
for (x, y) in itertools.product(list('12345678'), list('abcdefgh')):
if cell.isPlaceable(y + x, color):
new_cell = Board()
new_cell.update(cell_line)
new_cell.place(y + x, color)
new_state = new_cell.getCellLineList()
competitior = 'BLACK' if you != "BLACK" else 'WHITE'
(m, max_x, max_y) = maxBot(victory_cell, new_state, competitior,
alpha, beta, depth - 1)
m -= cur_weight
if m < minv:
minv = m
px = x
py = y
if minv <= alpha:
return (minv, px, py)
if minv < beta:
beta = minv
return minv, px, py
def BestMove(victory_cell, cur_state, you, depth):
global best
game = Board()
game.update(cur_state)
color = 'W' if you == "BLACK" else 'B'
px = None
py = None
bestVal = -9999
for (x, y) in itertools.product(list('12345678'), list('abcdefgh')):
if game.isPlaceable(y + x, color):
global best
best = 0
new_game = Board()
new_game.update(cur_state)
new_game.place(y + x, color)
new_state = new_game.getCellLineList()
moveVal = minimax(victory_cell, new_state, you, depth, True, -9999,
9999) + prior_spot(y + x) / 2
if moveVal > bestVal:
px = x
py = y
bestVal = moveVal
return px, py
def minimax(curState, depth, alpha, beta, isMax):
global bot
global color
global competitor
global c_color
game = Board()
game.update(curState)
result = evaluated(game)
if (result != 'CONTINUE'):
if (result == bot):
return 999999
elif result == 'DRAW':
return 0
else:
return -999999
score = 0
if (depth == 0):
b_nstep, c_nstep = numberOfStep(game, color)
t_p, b_p, c_p = positionScore(game, color)
score = findScoreCalculator(game, color)
v_score = viectoryCellScore(game, color)
if (b_p > c_p):
score += 50
if (t_p < 20):
if (b_nstep > c_nstep):
score += 150
else:
score += 50
else:
if (b_nstep > c_nstep):
score += 200
else:
score += 100
else:
# c_p > t_p
score -= 50
if (t_p < 20):
if (b_nstep > c_nstep):
score -= 50
else:
score -= 150
else:
if (b_nstep > c_nstep):
score -= 100
else:
score -= 200
score += v_score
if isMax:
return score
else:
return -score
if isMax:
best = -999999
listPosiblePositions = posiblePositions(game, color)
for step in listPosiblePositions:
newGame = Board()
newGame.update(curState)
newGame.place(step, color)
newState = newGame.getCellLineList()
best = max(best, minimax(newState, depth - 1, alpha, beta, False))
alpha = max(alpha, best)
if (beta <= alpha):
break
# print('max:', best)
return best
else:
best = 999999
listPosiblePositions = posiblePositions(game, c_color)
for step in listPosiblePositions:
newGame = Board()
newGame.update(curState)
newGame.place(step, c_color)
newState = newGame.getCellLineList()
best = min(best, minimax(newState, depth - 1, alpha, beta, True))
beta = min(beta, best)
if (beta <= alpha):
break
# print('min:', best)
return best
