| import gym | |
| from baselines import deepq | |
| def main(): | |
| env = gym.make("CartPole-v0") | |
| act = deepq.learn(env, network='mlp', total_timesteps=0, load_path="cartpole_model.pkl") | |
| while True: | |
| obs, done = env.reset(), False | |
| episode_rew = 0 | |
| while not done: | |
| env.render() | |
| obs, rew, done, _ = env.step(act(obs[None])[0]) | |
| episode_rew += rew | |
| print("Episode reward", episode_rew) | |
| if __name__ == '__main__': | |
| main() | |