Rainbow-DQN Agent playing LunarLander-v3
This is a trained model of a Rainbow-DQN agent playing LunarLander-v3.
Usage
create the conda env in https://github.com/GeneHit/drl_practice
conda create -n drl python=3.12
conda activate drl
python -m pip install -r requirements.txt
play with full model
# load the full model
model = load_from_hub(repo_id="winkin119/Rainbow-1d-LunarLander-v3", filename="full_model.pt")
# Create the environment.
env = gym.make("LunarLander-v3")
state, _ = env.reset()
action = model.action(state)
...
There is also a state dict version of the model, you can check the corresponding definition in the repo.
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Evaluation results
- mean_reward on LunarLander-v3self-reported281.35 +/- 22.43