CleanRL

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

[CleanRL @cleanrl_lib]

Yay!

[Costa Huang @vwxyzjn]

Happy to share my @nvidia internship's work: @cleanrl_lib's PPO now supports Isaac Gym!

📜 docs: https://t.co/sqZfBUlbAz

A short 🧵

[Chang Ye @yooceii]

Happy to share that @cleanrl_lib now supports Random Network Distillation + envpool, it's 3× faster than our first version without envpool and still have comparable performance to the original implementation, say 👋 to the long training time on hard-exploration games!
Details👇

[Costa Huang @vwxyzjn]

Thanks to @_joaogui1's awesome contribution 🙏, @cleanrl_lib now has a TD3 + JAX implementation that is 2-4x faster than the TD3 + @PyTorch equivalent 🔥. Running on TPU is now possible, too 🚀!

📜 docs: https://t.co/JXXh3xMGjY
💾 code: https://t.co/VXBnq4sh8G

A short 🧵1/x