pufferlib

What problem does it solve?

This Skill provides a high-performance reinforcement learning framework that dramatically speeds up environment simulation and agent training, allowing for faster experimentation and development of RL agents.

Core Features & Use Cases

• High-Performance Training: Achieve millions of steps per second with optimized PPO (PuffeRL).
• Vectorized Environments: Seamlessly integrates and vectorizes a vast array of existing RL environments (Gymnasium, PettingZoo, Atari, etc.).
• Custom Environment Creation: Offers tools and templates for building highly efficient custom environments.
• Use Case: Train complex RL agents on challenging tasks like Atari games or multi-agent scenarios in a fraction of the time compared to standard libraries.

Quick Start

Use the pufferlib skill to train a PPO agent on the procgen-coinrun environment using CUDA.