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Muddassir/
RL-Unit1

stable-baselines3

LunarLander-v2

deep-reinforcement-learning

reinforcement-learning

model-index

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Agent playing LunarLander-v2

This is a trained model of a ** ** agent playing LunarLander-v2 using the stable-baselines3 library.

Usage (with Stable-baselines3)

TODO: Add your code

python

from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub

model_name = "ppo-LunarLander-v2-Muddassir"
model.save(model_name)

eval_env = Monitor(gym.make("LunarLander-v2"))

mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=10, deterministic=True)

print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")

eval_env = Monitor(gym.make("LunarLander-v2"))
mean_reward, std_reward = evaluate_policy(model, eval_env, n_eval_episodes=10, deterministic=True)
print(f"mean_reward={mean_reward:.2f} +/- {std_reward}")

...

Muddassir/RL-Unit1

** ** Agent playing LunarLander-v2

Usage (with Stable-baselines3)

Muddassir/
RL-Unit1

Agent playing LunarLander-v2