def mctsNormal(self, board):
root = Node(None, None, None, self.opponent.color)
# set initial child layer
initial_moves = board.getAllValidMoves(self.pieces)
if initial_moves == []:
return None
for move in initial_moves:
#consider using piece size as first play urgency as initialVal
child = Node(move,
root,
self.color,
initialVal=move[0].size() * 10)
root.addChild(child)
num_simulations = 0
startTime = time.perf_counter()
while (self.resourcesAvailable(startTime)):
#selection phase
currentNode = Node.getMctsLeaf(root)
#make board accurate for current state
board.makeMovesInStack(currentNode.moveStack)
#expansion phase
useable_pieces = []
if currentNode.turnColor == self.color:
# opponents turn, use their pieces
useable_pieces = self.opponent.getPiecesNotIn(
currentNode.moveStack)
else:
#our turn, use our pieces
useable_pieces = self.getPiecesNotIn(currentNode.moveStack)
valid_moves = board.getAllValidMoves(useable_pieces)
if valid_moves == []:
#game in terminal moveStack for this player
pass
else:
# add all substates
for move in valid_moves:
child = Node(move,
currentNode,
move[0].color,
initialVal=move[0].size() * 10)
currentNode.addChild(child)
#simulation phase
res = self.playoutRandomGame(currentNode, board)
num_simulations += 1
#board is returned to initial state
#backpropogate
currentNode.backpropogate(res)
#select highest val node
node = Node.getMaxFirstLayer(root)
#Node.delTree(root)
#print(num_simulations, " simulations executed")
return node.move
