def _move_aggressive(self, g, chase_prob=.75):
if not np.random.binomial(1, p=chase_prob):
return self._move_random(g)
best_dist = self.grid.x_size + self.grid.y_size
best_pos = self.state.ghosts[g].pos
best_dir = -1
for d in range(self.action_space.n):
dist = Grid.directional_distance(self.state.agent_pos,
self.state.ghosts[g].pos, d)
new_pos = self._next_pos(self.state.ghosts[g].pos, d)
if dist <= best_dist and new_pos.is_valid() and can_move(
self.state.ghosts[g], d):
best_pos = new_pos
best_dist = dist
best_dir = d
self.state.ghosts[g].update(best_pos, best_dir)
def _move_defensive(self, g, defensive_prob=.5):
if np.random.binomial(
1, defensive_prob) and self.state.ghosts[g].direction >= 0:
self.state.ghosts[g].direction = -1
best_dist = self.grid.x_size + self.grid.y_size
best_pos = self.state.ghosts[g].pos
best_dir = -1
for d in range(self.action_space.n):
dist = Grid.directional_distance(self.state.agent_pos,
self.state.ghosts[g].pos, d)
new_pos = self._next_pos(self.state.ghosts[g].pos, d)
if dist >= best_dist and new_pos.is_valid() and can_move(
self.state.ghosts[g], d):
best_pos = new_pos
best_dist = dist
best_dir = d
self.state.ghosts[g].update(best_pos, best_dir)