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q-FrozenLake-v1-4x4-noSlippery
t3PbMvBN6SXv/q-FrozenLake-v1-4x4-noSlippery
q-FrozenLake-v1-4x4-noSlippery is a reinforcement learning model from t3PbMvBN6SXv. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.
This is a trained model of a Q-Learning agent playing {envid} .
Access
Public
Updated Jun 23, 2023
Repo size
914 B
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Repo makeup
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.mp431.1 KB · 90%
At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- Jun 23, 2023
- Updated
- Jun 23, 2023
- SHA
- 1c38c94b
Model card
From the Hugging Face model README
Q-Learning Agent playing1 {env_id}
This is a trained model of a Q-Learning agent playing {env_id} .
Usage
python
model = load_from_hub(repo_id="{repo_id}", filename="q-learning.pkl")
Don't forget to check if you need to add additional attributes (is_slippery=False etc)
env = gym.make(model["env_id"])
evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])
- Task
- Reinforcement Learning
- Created
- Jun 23, 2023
- Updated
- Jun 23, 2023