pufferlib

SKILL.md

PufferLib - High-Performance Reinforcement Learning

Overview

PufferLib is a high-performance reinforcement learning library designed for fast parallel environment simulation and training. It achieves training at millions of steps per second through optimized vectorization, native multi-agent support, and efficient PPO implementation (PuffeRL). The library provides the Ocean suite of 20+ environments and seamless integration with Gymnasium, PettingZoo, and specialized RL frameworks.

When to Use This Skill

Use this skill when:

Training RL agents with PPO on any environment (single or multi-agent)

Creating custom environments using the PufferEnv API

Optimizing performance for parallel environment simulation (vectorization)

Integrating existing environments from Gymnasium, PettingZoo, Atari, Procgen, etc.

Developing policies with CNN, LSTM, or custom architectures

Scaling RL to millions of steps per second for faster experimentation

Multi-agent RL with native multi-agent environment support

Core Capabilities