env.step中的return False在某种程度上可以是True吗?(健身房)

Question

当我试图弄清楚植绒env(来自健身房植绒(的重置条件时，我提出了一个问题："return False"能以某种方式返回True吗？？

核心代码是：

1:中的test_model.pyhttps://github.com/katetolstaya/multiagent_gnn_policies#available-算法

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：健身房环境代码：flocking_relative.pyhttps://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**, {}

由于while在test_model.py中循环以中断和重置env，done在某些方面应该是正确的。但是，env.step中的代码(代码第2部分(总是在done的位置返回False。

当env.step总是返回False时，这个循环是如何中断的？我已经测试并确认此代码运行良好，但是很难理解怎么做。

请帮助我在RL和健身房有经验的人提前非常感谢

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,
)

随着步骤数变为max_ episode_，步骤中的False返回True