>>> Box(low=-1.0, high=2.0, shape=(3, 4), dtype=np.float32) Box(3, 4) 如果不够直观,我们可以它sample出来看一下。 import numpy as np from gym.spaces.box import Box my_box = Box(low=-1.0, high=2.0, shape=(3, 4), dtype=np.float32) my_box_sample = my_box.sample() print...
gym.spaces.Space.contains(self, x) → bool 3. 将空间的shape作为不可变属性(类的属性)返回。 property Space.shape: Optional[Tuple[int, ...]] 4. 返回此空间的数据类型。 property gym.spaces.Space.dtype 5. ……(剩下的暂时没用到,下次再写捏) Box空间 class gym.spaces.Box(low: ~typing.Union...
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So i'm trying to perform some reinforcement learning in a custom environment using gym however I'm very confused as to how spaces.box works. What do each of the parameters mean? If I have a a game state that involves lots of information such as the hp of characters, their stats and a...
spaces.Box( low=low, high=high, dtype=venv.observation_space.dtype) if set(new_observation_spaces.keys()) == {None}: VecEnvWrapper.__init__(self, venv, observation_space=new_observation_spaces[None]) else: VecEnvWrapper.__init__(self, venv, observation_space=gym.spaces.Dict(new_...
python import gym import numpy as np class NavigationEnv(gym.Env): def __init__(self, start_pos=(0, 0), goal_pos=(10, 10), max_steps=100): self.start_pos = start_pos self.goal_pos = goal_pos self.max_steps = max_steps self.observation_space = gym.spaces.Box(low=np.array(...
count=0self.current_state=Noneself.action_space=spaces.Discrete(4)self.observation_space=spaces.Box...
master .github bin gym envs spaces __init__.py box.py dict.py discrete.py graph.py multi_binary.py multi_discrete.py sequence.py space.py text.py tuple.py utils.py utils vector wrappers __init__.py core.py error.py logger.py ...
这种内省可以帮助编写适用于许多不同环境的通用代码。box和discrete是最常见的空间。你可以从一个空间中取样,或者检查某物是否属于它: fromgymimportspaces space=spaces.Discrete(8)# Set with 8 elements {0, 1, 2, ..., 7}x=space.sample()assertspace.contains(x)assertspace.n==8 ...
环境 env 的观测空间用 env.observation_space 表示,动作空间用 env.action_space 表示。观测空间和动作空间既可以是离散空间(取值是有限个离散的值),也可以是连续空间(取值是连续的值)。在 Gym 库中,一般离散空间用 gym.spaces.Discrete 类表示,连续空间用 gym.spaces.Box 类表示。