def dijkstraEval(self, board_state, maximizer):
h = HexBoard(board_state.shape[0])
h.board = board_state
red_shortestPath = self.dijkstra(hexboard=h, color=h.RED)
blue_shortestPath = self.dijkstra(hexboard=h, color=h.BLUE)
freeReds = self.getFreeHexes(hexboard=h, path=red_shortestPath)
freeBlues = self.getFreeHexes(hexboard=h, path=blue_shortestPath)
heuristic_score = 0
if maximizer == h.RED:
heuristic_score = freeBlues - freeReds
else:
heuristic_score = freeReds - freeBlues
return heuristic_score
# def iterativeDeepening(self, node, maximizer):
# depth = 1
# end_time = datetime.now() + timedelta(seconds=3)
# For windows os
# while datetime.now() < end_time and not msvcrt.kbhit():
# bestScore = self.alphaBetaSearch(node, depth, -9999999, 9999999, isMaximizer=maximizer)
# depth = depth + 1
# return bestScore
def dijkstraEval(self, board_state, maximizer):
h = HexBoard(board_state.shape[0])
h.board = board_state
red_shortestPath = self.dijkstra(hexboard=h, color=h.RED)
blue_shortestPath = self.dijkstra(hexboard=h, color=h.BLUE)
freeReds = self.getFreeHexes(hexboard=h, path=red_shortestPath)
freeBlues = self.getFreeHexes(hexboard=h, path=blue_shortestPath)
if maximizer == h.RED:
heuristic_score = freeBlues - freeReds
else:
heuristic_score = freeReds - freeBlues
return heuristic_score
