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ppo-LunarLander-v2
Eugene-Bond/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from Eugene-Bond. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
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.mp4222 KB · 42%
At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- May 8, 2022
- Updated
- May 10, 2022
- SHA
- 9f0255c4
Model card
From the Hugging Face model README
PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
Usage (with Stable-baselines3)
from typing import Callable
def linear_schedule(initial_value: float) -> Callable[[float], float]:
def func(progress_remaining: float) -> float:
return progress_remaining * initial_value
return func
model = PPO(policy="MlpPolicy", env=env, verbose=1, n_epochs=10, learning_rate=linear_schedule(0.005), n_steps=1500)
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- May 8, 2022
- Updated
- May 10, 2022