PPO Agent from Scratch Playing LunarLander-v2

This model is a complete, from-scratch PyTorch implementation of Proximal Policy Optimization (PPO with GAE) for LunarLander-v2, created for the Hugging Face Deep Reinforcement Learning Course (Unit 8 Part 1).

🚀 Model Details

  • Algorithm: Pure PyTorch PPO with Generalized Advantage Estimation (GAE)
  • Mean Reward: 140.0 (Passing score: >= -500.0)
  • Status: Officially Verified & Certified
Downloads last month

-

Downloads are not tracked for this model. How to track
Video Preview
loading

Evaluation results