python - 可以在 env.step 中返回 False 以某种方式返回 True 吗？ (健身房)

Question

当我试图弄清楚 flocking env(来自 gym-flock)的重置条件时，我想到了这个问题:'return False' 能以某种方式返回 True 吗？？

核心代码是:

1: test_model.py 中 https://github.com/katetolstaya/multiagent_gnn_policies#available-algorithms

def test(args, actor_path, render=True):
# initialize gym env
env_name = args.get('env')
env = gym.make(env_name)
if isinstance(env.env, gym_flock.envs.FlockingRelativeEnv):
    env.env.params_from_cfg(args)

# use seed
seed = args.getint('seed')
env.seed(seed)
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)

# initialize params tuple
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
learner = DAGGER(device, args)
n_test_episodes = args.getint('n_test_episodes')
learner.load_model(actor_path, device)

**for _ in range(n_test_episodes):
    episode_reward = 0
    state = MultiAgentStateWithDelay(device, args, env.reset(), prev_state=None)
    done = False
    while not done:
        action = learner.select_action(state)
        next_state, reward, done, _ = env.step(action.cpu().numpy())
        next_state = MultiAgentStateWithDelay(device, args, next_state, prev_state=state)
        episode_reward += reward
        state = next_state
        if render:
            env.render()
    print(episode_reward)
env.close()**

2:gym环境代码:flocking_relative.py 中 https://github.com/katetolstaya/gym-flock/tree/stable/gym_flock/envs/flocking

    def step(self, u):

    #u = np.reshape(u, (-1, 2))
    assert u.shape == (self.n_agents, self.nu)
    #u = np.clip(u, a_min=-self.max_accel, a_max=self.max_accel)
    self.u = u * self.action_scalar

    # x position
    self.x[:, 0] = self.x[:, 0] + self.x[:, 2] * self.dt + self.u[:, 0] * self.dt * self.dt * 0.5
    # y position
    self.x[:, 1] = self.x[:, 1] + self.x[:, 3] * self.dt + self.u[:, 1] * self.dt * self.dt * 0.5
    # x velocity
    self.x[:, 2] = self.x[:, 2] + self.u[:, 0] * self.dt
    # y velocity
    self.x[:, 3] = self.x[:, 3] + self.u[:, 1] * self.dt

    self.compute_helpers()

    return (self.state_values, self.state_network), self.instant_cost(), **False**, {}

for while loop in test_model.py to break and reset env,在某些时候 done 应该是 True 。但是，env.step(代码第 2 部分)中的代码总是在 done 的位置返回 False。

当 env.step 总是返回 False 时，这个循环如何中断？我已经测试并确认这段代码工作正常，但是很难理解如何做。

请有RL和gym经验的帮帮我非常感谢您提前

Answer 1

https://github.com/katetolstaya/gym-flock/blob/stable/gym_flock/__init__.py#L65

在上面的文件中:

register(
    id='FlockingLeader-v0',
    entry_point='gym_flock.envs.flocking:FlockingLeaderEnv',
    max_episode_steps=200,
)

随着步数变为 max_episode_steps，步骤中的假返回真