创建并安装自己的OpenAI健身房环境

import gym
from gym import spaces

class MyEnv(gym.Env):
    def __init__(self):
        super(MyEnv, self).__init__()
        self.action_space = spaces.Discrete(2)  # 有两个动作：0和1
        self.observation_space = spaces.Box(low=0, high=1, shape=(2,), dtype=float)  # 观察空间是一个2维向量

    def step(self, action):
        assert self.action_space.contains(action), "Invalid action"
        observation = [action, action + 1]  # 简单的观察生成逻辑
        reward = action  # 简单的奖励生成逻辑
        done = False  # 假设这个环境没有终止状态
        info = {}  # 可以包含额外的信息
        return observation, reward, done, info

    def reset(self):
        return [0, 1]  # 重置观察空间到初始状态

    def render(self, mode='human'):
        pass  # 这里可以实现可视化逻辑，但在这个简单的例子中我们省略了它

# 注册环境
gym.envs.registration.register(
    id='MyEnv-v0',
    entry_point='my_env:MyEnv',
)

# 测试环境
env = gym.make('MyEnv-v0')
observation = env.reset()
for _ in range(10):
    action = env.action_space.sample()  # 随机选择一个动作
    observation, reward, done, info = env.step(action)
    print(f'Observation: {observation}, Reward: {reward}')