| tags: | |
| - Taxi-v3 | |
| - q-learning | |
| - reinforcement-learning | |
| - custom-implementation | |
| model-index: | |
| - name: q-Taxi-v3 | |
| results: | |
| - metrics: | |
| - type: mean_reward | |
| value: 7.54 +/- 2.73 | |
| name: mean_reward | |
| task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: Taxi-v3 | |
| type: Taxi-v3 | |
| # 使用**Q-Learning**智能体来玩**Taxi-v3** | |
| 这是一个使用**Q-Learning**训练有素的模型玩**Taxi-v3**. | |
| ## 用法 | |
| ```python | |
| model = load_from_hub(repo_id='sun1638650145/q-Taxi-v3', filename='q-learning.pkl') | |
| # 不要忘记检查是否需要添加额外的参数(例如is_slippery=False) | |
| env = gym.make(model['env_id']) | |
| evaluate_agent(env, model['max_steps'], model['n_eval_episodes'], model['qtable'], model['eval_seed']) | |
| ``` | |