def next_move(self, game):
""" Just looking at one step ahead for now
1. Generate all possible game states
2. Evaluate h = w1*f1 + w2*f2 + w3*f3...
3. Pick the best one (greedy breadth first search) """
game_states = heuristic.get_next_states(game,self.name,1)
h = []
for game_state in game_states[1]:
h.append((self.get_score(game_state), game_state))
next_node = max(h)[1][2]
return (next_node.x, next_node.y)
def next_minmax_move(self, game):
""" Just looking at one step ahead for now
1. Generate all possible game states
2. Evaluate h = w1*f1 + w2*f2 + w3*f3...
3. Pick the best one (greedy breadth first search) """
import copy
#print "Getting next states..."
game_states = heuristic.get_next_states(copy.deepcopy(game),self.depth)
#print "Searching..."
next_score, next_game = self.minimax_search(game_states, self.depth)
#print next_score, next_game
next_node = next_game[2]
#print "Found %s." % str((next_node.x, next_node.y))
return (next_node.x, next_node.y)
