我的任务是制作一个AI代理，该代理将学习使用ML玩视频游戏。我想使用OpenAI Gym创建一个新环境，因为我不想使用现有环境。如何创建新的自定义环境？
另外，在没有OpenAI Gym的帮助下，我还有其他方法可以使AI Agent玩特定的视频游戏吗？
最佳答案
请参阅我的 banana-gym 以了解非常小的环境。
创建新环境
请参见存储库的主页:
https://github.com/openai/gym/blob/master/docs/creating-environments.md
这些步骤是:
它应该看起来像这样
gym-foo/
README.md
setup.py
gym_foo/
__init__.py
envs/
__init__.py
foo_env.py
foo_extrahard_env.py
有关其内容，请单击上面的链接。这里没有提到的细节特别是
foo_env.py中的某些函数应如何显示。查看示例和gym.openai.com/docs/会有所帮助。这是一个例子:class FooEnv(gym.Env):
metadata = {'render.modes': ['human']}
def __init__(self):
pass
def _step(self, action):
"""
Parameters
----------
action :
Returns
-------
ob, reward, episode_over, info : tuple
ob (object) :
an environment-specific object representing your observation of
the environment.
reward (float) :
amount of reward achieved by the previous action. The scale
varies between environments, but the goal is always to increase
your total reward.
episode_over (bool) :
whether it's time to reset the environment again. Most (but not
all) tasks are divided up into well-defined episodes, and done
being True indicates the episode has terminated. (For example,
perhaps the pole tipped too far, or you lost your last life.)
info (dict) :
diagnostic information useful for debugging. It can sometimes
be useful for learning (for example, it might contain the raw
probabilities behind the environment's last state change).
However, official evaluations of your agent are not allowed to
use this for learning.
"""
self._take_action(action)
self.status = self.env.step()
reward = self._get_reward()
ob = self.env.getState()
episode_over = self.status != hfo_py.IN_GAME
return ob, reward, episode_over, {}
def _reset(self):
pass
def _render(self, mode='human', close=False):
pass
def _take_action(self, action):
pass
def _get_reward(self):
""" Reward is given for XY. """
if self.status == FOOBAR:
return 1
elif self.status == ABC:
return self.somestate ** 2
else:
return 0
使用你的环境
import gym
import gym_foo
env = gym.make('MyEnv-v0')
例子
关于machine-learning - 如何在OpenAI中创建新的体育馆环境？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/45068568/