Pufferlib
원문: pufferlib
This skill should be used when working with reinforcement learning tasks including high-performance RL training, custom environment development, vectorized parallel simulation, multi-agent systems, or integration with existing RL environments (Gymnasium, PettingZoo, Atari, Procge
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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…
실행 시 본인 API 키(BYOK)로 동작하며, 모델 비용은 사용자 계정에서 직접 결제됩니다.