metadata
tags:
- CartPole-v1
- q-learning
- reinforcement-learning
- custom-implementation
model-index:
- name: Q-Cartpole-v1
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: CartPole-v1
type: CartPole-v1
metrics:
- type: mean_reward
value: 88.22 +/- 17.67
name: mean_reward
verified: false
Q-Learning Agent playing CartPole-v1
This is a trained model of a Q-Learning agent playing CartPole-v1 .
Usage
model = load_from_hub(repo_id="artbreguez/Q-Cartpole-v1", filename="q-learning.pkl")
env = gym.make(model["env_id"])
evaluate_agent(env, model["max_steps"], model["n_eval_episodes"], model["qtable"], model["eval_seed"])