def rollout_policy(self, state):
# random policy
# action = random.choice(self.action_list)
# DQNs policy
state = self.getStateRepresentation(state)
action_ind = BaseDynaAgent.policy(self, state)
action = self.action_list[action_ind.item()]
return action
def policy(self, state):
if self.episode_counter % 2 == 1:
action, sub_tree = None, None
for i in range(self.num_iterations):
action, sub_tree = self.MCTS_iteration()
# self.render_tree()
self.subtree_node = sub_tree
action = torch.from_numpy(np.array(
[self.getActionIndex(action)])).unsqueeze(0).to(self.device)
else:
action = BaseDynaAgent.policy(self, state)
return action
