def alphaBeta(board, color,reverse, depth, strategy, alpha = -sys.maxint, beta = sys.maxint) :
if depth == 0 :
if strategy == 1 :
return evalue(board)
else:
return value(board)
moves = []
for i in range(8) :
for j in range(8) :
if gameplay.valid(board, color, (i,j)) :
moves.append((i,j))
if len(moves) == 0 :
if (gameplay.gameOver(board)) :
return evalue(board)
else:
if (color == "B" and not reverse) or (color == "W" and reverse) :
newBoard = deepcopy(board)
gameplay.doMove(newBoard,color,'pass')
val = max(alpha, alphaBeta(newBoard, gameplay.opponent(color), reverse, depth - 1, strategy, alpha, beta))
return val
else :
newBoard = deepcopy(board)
gameplay.doMove(newBoard,color,'pass')
val = min(beta, alphaBeta(newBoard, gameplay.opponent(color), reverse, depth - 1, strategy, alpha, beta))
return val
else:
if (color == "B" and not reverse) or (color == "W" and reverse) :
for move in moves :
newBoard = deepcopy(board)
gameplay.doMove(newBoard,color,move)
alpha = max(alpha, alphaBeta(newBoard, gameplay.opponent(color), reverse, depth - 1, strategy, alpha, beta))
if beta <= alpha :
break
return alpha
else :
for move in moves :
newBoard = deepcopy(board)
gameplay.doMove(newBoard,color,move)
beta = min(beta, alphaBeta(newBoard, gameplay.opponent(color), reverse, depth - 1, strategy, alpha, beta))
if beta <= alpha:
break
return beta
def maxvalue(board, color, ori_color, deepest, search_depth, alpha, beta):
search_depth = search_depth + 1
if search_depth == deepest or gameplay.gameOver(board):
return calculate(board, search_depth, ori_color)
moves = []
bestmove = "pass"
for i in range(8):
for j in range(8):
if gameplay.valid(board, color, (i, j)):
moves.append((i, j))
v = -float('inf')
if len(moves) == 0:
if search_depth == 1:
return float('inf'), "pass"
else:
return float('inf')
# print 'max',search_depth
# print moves
for move in moves:
newBoard = deepcopy(board)
gameplay.doMove(newBoard, color, move)
min_value = minvalue(newBoard, gameplay.opponent(color), ori_color,
deepest, search_depth, alpha, beta)
if min_value > v:
# if search_depth==1:
# print "v=",v,"min_value=",min_value
v = min_value
if search_depth == 1:
bestmove = move
if v >= beta:
if search_depth == 1:
return v, bestmove
else:
return v
alpha = max(alpha, v)
if search_depth == 1:
return v, bestmove
else:
return v
def maxvalue(board,color,ori_color,deepest,search_depth,alpha,beta):
search_depth=search_depth+1
if search_depth == deepest or gameplay.gameOver(board):
return calculate(board,search_depth,ori_color)
moves=[]
bestmove="pass"
for i in range(8):
for j in range(8):
if gameplay.valid(board, color, (i,j)):
moves.append((i,j))
v=-float('inf')
if len(moves) == 0:
if search_depth==1:
return float('inf'),"pass"
else:
return float('inf')
# print 'max',search_depth
# print moves
for move in moves:
newBoard = deepcopy(board)
gameplay.doMove(newBoard,color,move)
min_value=minvalue(newBoard,gameplay.opponent(color),ori_color,deepest,search_depth,alpha,beta)
if min_value>v:
# if search_depth==1:
# print "v=",v,"min_value=",min_value
v=min_value
if search_depth==1:
bestmove=move
if v>=beta:
if search_depth==1:
return v,bestmove
else:
return v
alpha=max(alpha,v)
if search_depth==1:
return v,bestmove
else:
return v
def alpha_beta_search(node, alpha, beta, timeout):
if timeout(): return node.value() # Timeout do nothing
if (node.depth == 0):
if (god.gameOver(node.board)):
return node.end_value()
else:
return node.value()
nextMoves = node.validMoves()
if (len(nextMoves) == 0): nextMoves = ['pass'] # Game not end, we can pass on.
for pos in nextMoves:
# init next child node
nextnode = TreeNode(node)
god.doMove(nextnode.board, node.color, pos)
# Update from children
res = alpha_beta_search(nextnode, alpha, beta, timeout)
# Update bounds
if (node.color == 'W') != (node.reversed): # min
if betterThan(beta, res, node.color, node.reversed):
beta = res
else: # max
if betterThan(alpha, res, node.color, node.reversed):
alpha = res
# Pruning
if (alpha >= beta):
#if VERBOSE: print "==Pruning %f..%f in %d" % (alpha, beta, node.depth)
break
if (node.color == 'W') != (node.reversed): # min
return beta
else:
return alpha
def endState(state):
return gameplay.gameOver(state)
def endState(state):
return gameplay.gameOver(state)
def alphaBeta(board,
color,
reverse,
depth,
strategy,
alpha=-sys.maxint,
beta=sys.maxint):
if depth == 0:
if strategy == 1:
return evalue(board)
else:
return value(board)
moves = []
for i in range(8):
for j in range(8):
if gameplay.valid(board, color, (i, j)):
moves.append((i, j))
if len(moves) == 0:
if (gameplay.gameOver(board)):
return evalue(board)
else:
if (color == "B" and not reverse) or (color == "W" and reverse):
newBoard = deepcopy(board)
gameplay.doMove(newBoard, color, 'pass')
val = max(
alpha,
alphaBeta(newBoard, gameplay.opponent(color), reverse,
depth - 1, strategy, alpha, beta))
return val
else:
newBoard = deepcopy(board)
gameplay.doMove(newBoard, color, 'pass')
val = min(
beta,
alphaBeta(newBoard, gameplay.opponent(color), reverse,
depth - 1, strategy, alpha, beta))
return val
else:
if (color == "B" and not reverse) or (color == "W" and reverse):
for move in moves:
newBoard = deepcopy(board)
gameplay.doMove(newBoard, color, move)
alpha = max(
alpha,
alphaBeta(newBoard, gameplay.opponent(color), reverse,
depth - 1, strategy, alpha, beta))
if beta <= alpha:
break
return alpha
else:
for move in moves:
newBoard = deepcopy(board)
gameplay.doMove(newBoard, color, move)
beta = min(
beta,
alphaBeta(newBoard, gameplay.opponent(color), reverse,
depth - 1, strategy, alpha, beta))
if beta <= alpha:
break
return beta