Rl

stable-baselines3 skill guide for Machine Learning workflows: train RL agents, wire Gymnasium environments, and choose PPO, SAC, DQN, TD3, DDPG, or A2C with less guesswork. Best for standard single-agent reinforcement learning, quick prototyping, and practical stable-baselines3 usage.

pufferlib is a high-performance reinforcement learning skill for fast parallel simulation, vectorized rollouts, and multi-agent training. Use this pufferlib guide to install, understand pufferlib usage, and adapt RL pipelines with Gymnasium, PettingZoo, Atari, Procgen, or NetHack-style environments. Ideal for code generation focused on throughput and scalable PPO workflows.