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computational-chemistryresearch

stable-baselines3

Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

lamm-mit
maintainer
lamm-mit
آخر تحديث 3/14/2026
النجوم
156
التفرعات
35
quick start

Installation and usage

Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

التثبيت
$ install --globalskills.sh
الاستخدام

بعد التثبيت، يمكنك استخدام هذه المهارة بتشغيل الأمر التالي في الطرفية:

skills use stable-baselines3