
      # 使用**Q-Learning**智能体来玩**FrozenLake-v1**
      这是一个使用**Q-Learning**训练有素的模型玩**FrozenLake-v1**.
      
      ## 用法
      ```python
      model = load_from_hub(repo_id='sun1638650145/q-FrozenLake-v1-4x4-noSlippery', 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'])
      
      ```
      
{"tags": ["FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation"], "model-index": [{"name": "q-FrozenLake-v1-4x4-noSlippery", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "FrozenLake-v1-4x4-no_slippery", "type": "FrozenLake-v1-4x4-no_slippery"}, "metrics": [{"type": "mean_reward", "value": "1.00 +/- 0.00", "name": "mean_reward"}]}]}]}
FrozenLake-v1-4x4-no_slippery q-learning reinforcement-learning custom-implementation model-index region:us
TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 


      # 使用Q-Learning智能体来玩FrozenLake-v1
      这是一个使用Q-Learning训练有素的模型玩FrozenLake-v1.
      
      ## 用法
      
      
# 使用Q-Learning智能体来玩FrozenLake-v1
      这是一个使用Q-Learning训练有素的模型玩FrozenLake-v1.
      
      ## 用法
TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 
 # 使用Q-Learning智能体来玩FrozenLake-v1
      这是一个使用Q-Learning训练有素的模型玩FrozenLake-v1.
      
      ## 用法
passage: TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 
# 使用Q-Learning智能体来玩FrozenLake-v1
      这是一个使用Q-Learning训练有素的模型玩FrozenLake-v1.
      
      ## 用法