

  # **Q-Learning** Agent playing1 **FrozenLake-v1**
  This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** .

  ## Usage

{'env_id': 'FrozenLake-v1',

 'max_steps': 99,
 
 'n_training_episodes': 10000,
 
 'n_eval_episodes': 100,
 
 'eval_seed': [],
 
 'learning_rate': 0.7,
 
 'gamma': 0.95,
 
 'max_epsilon': 1.0,
 
 'min_epsilon': 0.05,
 
 'decay_rate': 0.0005,
 
 'qtable': array([[
 
         0.73509189, 0.77378094, 0.77378094, 0.73509189],
 
        [0.73509189, 0.        , 0.81450625, 0.77378094],
        
        [0.77378094, 0.857375  , 0.77378094, 0.81450625],
        
        [0.81450625, 0.        , 0.77378094, 0.77378094],
        
        [0.77378094, 0.81450625, 0.        , 0.73509189],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.        , 0.81450625],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.81450625, 0.        , 0.857375  , 0.77378094],
        
        [0.81450625, 0.9025    , 0.9025    , 0.        ],
        
        [0.857375  , 0.95      , 0.        , 0.857375  ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.95      , 0.857375  ],
        
        [0.9025    , 0.95      , 1.        , 0.9025    ],
        
        [0.        , 0.        , 0.        , 0.        ]])}
  
{"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", "verified": false}]}]}]}
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 



  # Q-Learning Agent playing1 FrozenLake-v1
  This is a trained model of a Q-Learning agent playing FrozenLake-v1 .

  ## Usage

{'env_id': 'FrozenLake-v1',

 'max_steps': 99,
 
 'n_training_episodes': 10000,
 
 'n_eval_episodes': 100,
 
 'eval_seed': [],
 
 'learning_rate': 0.7,
 
 'gamma': 0.95,
 
 'max_epsilon': 1.0,
 
 'min_epsilon': 0.05,
 
 'decay_rate': 0.0005,
 
 'qtable': array([[
 
         0.73509189, 0.77378094, 0.77378094, 0.73509189],
 
        [0.73509189, 0.        , 0.81450625, 0.77378094],
        
        [0.77378094, 0.857375  , 0.77378094, 0.81450625],
        
        [0.81450625, 0.        , 0.77378094, 0.77378094],
        
        [0.77378094, 0.81450625, 0.        , 0.73509189],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.        , 0.81450625],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.81450625, 0.        , 0.857375  , 0.77378094],
        
        [0.81450625, 0.9025    , 0.9025    , 0.        ],
        
        [0.857375  , 0.95      , 0.        , 0.857375  ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.95      , 0.857375  ],
        
        [0.9025    , 0.95      , 1.        , 0.9025    ],
        
        [0.        , 0.        , 0.        , 0.        ]])}
  
# Q-Learning Agent playing1 FrozenLake-v1
  This is a trained model of a Q-Learning agent playing FrozenLake-v1 .

  ## Usage

{'env_id': 'FrozenLake-v1',

 'max_steps': 99,
 
 'n_training_episodes': 10000,
 
 'n_eval_episodes': 100,
 
 'eval_seed': [],
 
 'learning_rate': 0.7,
 
 'gamma': 0.95,
 
 'max_epsilon': 1.0,
 
 'min_epsilon': 0.05,
 
 'decay_rate': 0.0005,
 
 'qtable': array([[
 
         0.73509189, 0.77378094, 0.77378094, 0.73509189],
 
        [0.73509189, 0.        , 0.81450625, 0.77378094],
        
        [0.77378094, 0.857375  , 0.77378094, 0.81450625],
        
        [0.81450625, 0.        , 0.77378094, 0.77378094],
        
        [0.77378094, 0.81450625, 0.        , 0.73509189],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.        , 0.81450625],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.81450625, 0.        , 0.857375  , 0.77378094],
        
        [0.81450625, 0.9025    , 0.9025    , 0.        ],
        
        [0.857375  , 0.95      , 0.        , 0.857375  ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.95      , 0.857375  ],
        
        [0.9025    , 0.95      , 1.        , 0.9025    ],
        
        [0.        , 0.        , 0.        , 0.        ]])}
TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 
 # Q-Learning Agent playing1 FrozenLake-v1
  This is a trained model of a Q-Learning agent playing FrozenLake-v1 .

  ## Usage

{'env_id': 'FrozenLake-v1',

 'max_steps': 99,
 
 'n_training_episodes': 10000,
 
 'n_eval_episodes': 100,
 
 'eval_seed': [],
 
 'learning_rate': 0.7,
 
 'gamma': 0.95,
 
 'max_epsilon': 1.0,
 
 'min_epsilon': 0.05,
 
 'decay_rate': 0.0005,
 
 'qtable': array([[
 
         0.73509189, 0.77378094, 0.77378094, 0.73509189],
 
        [0.73509189, 0.        , 0.81450625, 0.77378094],
        
        [0.77378094, 0.857375  , 0.77378094, 0.81450625],
        
        [0.81450625, 0.        , 0.77378094, 0.77378094],
        
        [0.77378094, 0.81450625, 0.        , 0.73509189],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.        , 0.81450625],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.81450625, 0.        , 0.857375  , 0.77378094],
        
        [0.81450625, 0.9025    , 0.9025    , 0.        ],
        
        [0.857375  , 0.95      , 0.        , 0.857375  ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.95      , 0.857375  ],
        
        [0.9025    , 0.95      , 1.        , 0.9025    ],
        
        [0.        , 0.        , 0.        , 0.        ]])}
TAGS
#FrozenLake-v1-4x4-no_slippery #q-learning #reinforcement-learning #custom-implementation #model-index #region-us 
# Q-Learning Agent playing1 FrozenLake-v1
  This is a trained model of a Q-Learning agent playing FrozenLake-v1 .

  ## Usage

{'env_id': 'FrozenLake-v1',

 'max_steps': 99,
 
 'n_training_episodes': 10000,
 
 'n_eval_episodes': 100,
 
 'eval_seed': [],
 
 'learning_rate': 0.7,
 
 'gamma': 0.95,
 
 'max_epsilon': 1.0,
 
 'min_epsilon': 0.05,
 
 'decay_rate': 0.0005,
 
 'qtable': array([[
 
         0.73509189, 0.77378094, 0.77378094, 0.73509189],
 
        [0.73509189, 0.        , 0.81450625, 0.77378094],
        
        [0.77378094, 0.857375  , 0.77378094, 0.81450625],
        
        [0.81450625, 0.        , 0.77378094, 0.77378094],
        
        [0.77378094, 0.81450625, 0.        , 0.73509189],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.        , 0.81450625],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.81450625, 0.        , 0.857375  , 0.77378094],
        
        [0.81450625, 0.9025    , 0.9025    , 0.        ],
        
        [0.857375  , 0.95      , 0.        , 0.857375  ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.        , 0.        , 0.        ],
        
        [0.        , 0.9025    , 0.95      , 0.857375  ],
        
        [0.9025    , 0.95      , 1.        , 0.9025    ],
        
        [0.        , 0.        , 0.        , 0.        ]])}