def update_task_influence(self, influence):
'update dynamic goal values depending on current situation'
# assess situation
my_tiles = [loc for loc in influence.map if math.fabs(influence.map[loc]) > 0.01]
total_tile_count = self.gamestate.cols * self.gamestate.rows
self.winning_percentage = float(len(my_tiles))/total_tile_count
debug_logger.debug('currently owning %d in %d tiles, ratio: %f' %
(len(my_tiles), total_tile_count, self.winning_percentage))
debug_logger.debug('my ant_hill is at %s' % str(self.gamestate.my_hills()))
debug_logger.debug('known enemy hill: %s' % str(self.gamestate.enemy_hills()))
# alter aggressiveness as situation changes
self.my_fighter_value = 0 - 1 - (self.winning_percentage / 0.3 % 1)
self.enemy_ant_value = 0 - (self.winning_percentage / 0.3 % 1) * 2
# hill defense
if len(self.gamestate.my_hills()) == 1:
my_hill = self.gamestate.my_hills()[0]
for enemy_ninja in [ant for ant, owner in self.gamestate.enemy_ants() if self.gamestate.manhattan_distance(my_hill, ant) < 8]:
influence.map[my_hill] += self.enemy_ninja_value
## create route task
# find area with highest ant density
high_dense_loc = max(influence.map, key=influence.map.get)
high_dense_val = influence.map[high_dense_loc]
# find closest desirable area using bfs
route = path.bfs_findtask(self.gamestate, influence, high_dense_loc, 500)
# setup task, only long distance ones count
if len(route) > 8:
self.route_task = (route, high_dense_val)
debug_logger.debug('found route_task: %s' % str(self.route_task))
def update_task_influence(self, influence):
'update dynamic goal values depending on current situation'
# assess situation
my_tiles = [loc for loc in influence.map if math.fabs(influence.map[loc]) > 0.01]
total_tile_count = self.gamestate.cols * self.gamestate.rows
self.winning_percentage = len(my_tiles), total_tile_count, float(len(my_tiles))/total_tile_count
logging.debug('currently owning %d in %d tiles, ratio: %f' % self.winning_percentage)
logging.debug('my ant_hill is at %s' % str(self.gamestate.my_hills()))
logging.debug('known enemy hill: %s' % str(self.gamestate.enemy_hills()))
# if winning
# if losing
# unsure
## create route task
# find area with highest ant density
high_dense_loc = max(influence.map, key=influence.map.get)
high_dense_val = influence.map[high_dense_loc]
# find closest desirable area using bfs
route = path.bfs_findtask(self.gamestate, influence, high_dense_loc, 500)
# setup task
if len(route) > 3:
self.route_task = (route, high_dense_val)
logging.debug('found route_task: %s' % str(self.route_task))
