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q-FrozenLake-v1-4x4-Slippery_param2
IvanTi/q-FrozenLake-v1-4x4-Slippery_param2
q-FrozenLake-v1-4x4-Slippery_param2 is a reinforcement learning model from IvanTi. 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 FrozenLake-v1 .
Access
Public
Updated May 24, 2022
Repo size
130 KB
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0
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Repo makeup
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.mp453.1 KB · 94%
At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- May 24, 2022
- Updated
- May 24, 2022
- SHA
- 78457a48
Model card
From the Hugging Face model README
Q-Learning Agent playing FrozenLake-v1
This is a trained model of a Q-Learning agent playing FrozenLake-v1 .
Usage
model = load_from_hub(repo_id="IvanTi/q-FrozenLake-v1-4x4-Slippery_param2", 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
- May 24, 2022
- Updated
- May 24, 2022