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RLlib

swMATH ID: 31153
Software Authors: The Ray Team Revision; Eric Liang, Richard Liaw, Philipp Moritz, Robert Nishihara, Roy Fox, Ken Goldberg, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
Description: RLlib: Scalable Reinforcement Learning. RLlib is an open-source library for reinforcement learning that offers both high scalability and a unified API for a variety of applications. RLlib natively supports TensorFlow, TensorFlow Eager, and PyTorch, but most of its internals are framework agnostic.
Homepage: https://ray.readthedocs.io/en/latest/rllib.html
Keywords: Artificial Intelligence; arXiv_cs.AI; Cluster Computing; arXiv_cs.DC; Machine Learning; arXiv_cs.LG; Reinforcement Learning
Related Software: OpenAI Gym; Python; PyTorch; Dopamine; Stable Baselines; rlpyt; ChainerRL; Horizon; Catalyst.RL; MuJoCo; ONNX; Tensorforce; TensorFlow; RLgraph; GitHub; OpenGraphGym; Ecole; graphenv; Isaac Gym; TensorBoard
Referenced in: 2 Publications

Standard Articles

1 Publication describing the Software Year
RLlib: Abstractions for Distributed Reinforcement Learning
Eric Liang, Richard Liaw, Philipp Moritz, Robert Nishihara, Roy Fox, Ken Goldberg, Joseph E. Gonzalez, Michael I. Jordan, Ion Stoica
2017

Referenced in 1 Field

2 Computer science (68-XX)

Referencing Publications by Year