RLE-Foundation/rllte
A reinforcement learning library providing training algorithms, intrinsic reward modules, and benchmarks on PyTorch.
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RLLTE is a reinforcement learning research library that implements modern RL algorithms including PPO, Phasic Policy Gradient, and DrQ-v2. It provides intrinsic reward modules for exploration and benchmarks on environments like DeepMind Control Suite, ProcGen, and PyBullet. The library offers GPU and NPU acceleration for training and supports algorithm decoupling for modular experimentation.
Frequently asked
- What is RLE-Foundation/rllte?
- A reinforcement learning library providing training algorithms, intrinsic reward modules, and benchmarks on PyTorch.
- Is rllte open source?
- Yes — RLE-Foundation/rllte is open source, released under the MIT license.
- What language is rllte written in?
- RLE-Foundation/rllte is primarily written in Python.
- How popular is rllte?
- RLE-Foundation/rllte has 470 stars on GitHub.
- Where can I find rllte?
- RLE-Foundation/rllte is on GitHub at https://github.com/RLE-Foundation/rllte.