Downloads · 30 days
0
q-learning-FrozenLake-v1-4x4-slipperyparams_v2
linker81/q-learning-FrozenLake-v1-4x4-slipperyparams_v2
q-learning-FrozenLake-v1-4x4-slipperyparams_v2 is a reinforcement learning model from linker81. 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-v1-4x4-slippery .
Access
Public
Updated May 22, 2022
Repo size
37.1 KB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.mp436.2 KB · 92%
At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- May 22, 2022
- Updated
- May 22, 2022
- SHA
- fb80cbc5
Model card
From the Hugging Face model README
Q-Learning Agent playing FrozenLake-v1-4x4-slippery
This is a trained model of a Q-Learning agent playing FrozenLake-v1-4x4-slippery .
Usage
model = load_from_hub(repo_id="linker81/q-learning-FrozenLake-v1-4x4-slipperyparams_v2", 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 22, 2022
- Updated
- May 22, 2022