def search(self, current_state, info_set, init_max_depth):
'''
@param info_set: info set of current_state
'''
# start iterative search
curr_max_depth = init_max_depth
# print "time left", end_time - time.clock(), "d=", curr_max_depth
while True:
EndTimer.check("start search")
print "time left", EndTimer.time_left(), "d=", curr_max_depth
alg = SmartAlphaBetaSearch(self.player, self.utility, self.turn_cache, self.winner_check,self.use_quads)
self.res_action, self.res_state, self.res_info_set = alg.search(current_state, curr_max_depth, info_set)
curr_max_depth += self.depth_delta #TODO: TODO
def search(self, current_state, info_set, init_max_depth):
'''
@param info_set: info set of current_state
'''
# start iterative search
curr_max_depth = init_max_depth
#print init_max_depth
# print "time left", end_time - time.clock(), "d=", curr_max_depth
alg = SmartAlphaBetaSearch(self.player, self.utility, self.turn_cache, self.time_statistics, self.node_statistics, self.winner_check, )
while True:
EndTimer.check("start search")
self.node_statistics.start_monitor(curr_max_depth)
r = alg.search(current_state, curr_max_depth, info_set)
self.node_statistics.stop_monitor(curr_max_depth)
self.res_action, self.res_state, self.res_info_set = r
#print "Solution at depth:", curr_max_depth, " time left:", EndTimer.time_left()
curr_max_depth += self.depth_delta
