hongbo-miao/hongbomiao.com

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machine-learning/reinforcement-learning/cart-pole/src/main.py

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import gymnasium as gym


def main() -> None:
    env = gym.make("CartPole-v1")
    observation, info = env.reset(seed=42)
    print(observation, info)
    for _ in range(1000):
        action = env.action_space.sample()
        observation, reward, terminated, truncated, info = env.step(action)

        if terminated or truncated:
            observation, info = env.reset()
            print(observation, info)
    env.close()


if __name__ == "__main__":
    main()