def __init__(self, board, broadth=None):
self._board = board
self._moveSortHandler = MoveSortHandler(board, broadth)
return
def __init__(self,board,broadth=None):
self._board = board
self._moveSortHandler = MoveSortHandler(board,broadth)
return
class SearchHandler:
"""
MiniMax search algorithm with alpha-beta pruning.
"""
def __init__(self, board, broadth=None):
self._board = board
self._moveSortHandler = MoveSortHandler(board, broadth)
return
def getBestMove(self, depth=4):
self._board.stackClear()
(best_move, value) = self.alphaBeta(True, depth, -float("inf"),
float("inf"))
return best_move
def alphaBeta(self, isMax, depth, alpha, beta):
"""
return (best_move,alpha/beta)
"""
# Max = Computer = black
# Because computer is doing the search, so it tries to maximize its winning possiblity
# print " now the depth is ",depth
if depth == 0 or self._board.checkOver():
# reach the search depth limit or terminal node
# print " now returning the last_move and calcValue",self._board._lastMove,self._board.calcValue()
return (self._board._lastMove, self._board.calcValue())
legalMoves = self._board.allLegalMoves(
isMax) # isMax = Computer =Black side
sortedLegalMoves = self._moveSortHandler.sortLegalMoves(legalMoves)
best_move = None
if isMax:
for move in sortedLegalMoves:
self._board.makeMove(move)
# print "Black: Search after makeMove"
# self._board.printBoard()
(childMove,
childValue) = self.alphaBeta(False, depth - 1, alpha, beta)
self._board.unmakeMove(move)
# print "Black: Search after UNmakeMove"
# self._board.printBoard()
if alpha < childValue:
# (best_move,alpha) = (childMove,childValue)
alpha = childValue
best_move = move
if alpha >= beta:
# print "alpha cutoff pruning here"
break
return (best_move, alpha)
else: #Red side - Player
for move in sortedLegalMoves:
self._board.makeMove(move)
# print "Red: Search after makeMove"
# self._board.printBoard()
(childMove,
childValue) = self.alphaBeta(True, depth - 1, alpha, beta)
self._board.unmakeMove(move)
# print "Red: Search after UNmakeMove"
# self._board.printBoard()
if beta > childValue:
# (best_move,beta) = (childMove,childValue)
beta = childValue
best_move = move
if alpha >= beta:
#******* print "beta cutoff pruning here"
break
return (best_move, beta)
class SearchHandler:
"""
MiniMax search algorithm with alpha-beta pruning.
"""
def __init__(self,board,broadth=None):
self._board = board
self._moveSortHandler = MoveSortHandler(board,broadth)
return
def getBestMove(self,depth=4):
self._board.stackClear()
(best_move,value) = self.alphaBeta(True,depth,-float("inf"),float("inf"))
return best_move
def alphaBeta(self,isMax,depth,alpha,beta):
"""
return (best_move,alpha/beta)
"""
# Max = Computer = black
# Because computer is doing the search, so it tries to maximize its winning possiblity
# print " now the depth is ",depth
if depth == 0 or self._board.checkOver():
# reach the search depth limit or terminal node
# print " now returning the last_move and calcValue",self._board._lastMove,self._board.calcValue()
return (self._board._lastMove,self._board.calcValue())
legalMoves = self._board.allLegalMoves(isMax)# isMax = Computer =Black side
sortedLegalMoves = self._moveSortHandler.sortLegalMoves(legalMoves)
best_move = None
if isMax:
for move in sortedLegalMoves:
self._board.makeMove(move)
# print "Black: Search after makeMove"
# self._board.printBoard()
(childMove,childValue) = self.alphaBeta(False,depth-1,alpha,beta)
self._board.unmakeMove(move)
# print "Black: Search after UNmakeMove"
# self._board.printBoard()
if alpha < childValue:
# (best_move,alpha) = (childMove,childValue)
alpha = childValue
best_move = move
if alpha >=beta:
# print "alpha cutoff pruning here"
break
return (best_move,alpha)
else: #Red side - Player
for move in sortedLegalMoves:
self._board.makeMove(move)
# print "Red: Search after makeMove"
# self._board.printBoard()
(childMove,childValue) = self.alphaBeta(True,depth-1,alpha,beta)
self._board.unmakeMove(move)
# print "Red: Search after UNmakeMove"
# self._board.printBoard()
if beta > childValue:
# (best_move,beta) = (childMove,childValue)
beta = childValue
best_move = move
if alpha >=beta:
#******* print "beta cutoff pruning here"
break
return (best_move,beta)