mirror of
https://github.com/wassname/ray.git
synced 2026-06-27 19:16:19 +08:00
efce49cfbcdde84de3a1f71130b38948bea47a49
[rllib] Move policy gradient and evolution strategies algorithms from examples/ to ray/rllib/ (#694)
[rllib] Move policy gradient and evolution strategies algorithms from examples/ to ray/rllib/ (#694)
Implement object table notification subscriptions and switch to using Redis modules for object table. (#134)
Ray
===
.. image:: https://travis-ci.org/ray-project/ray.svg?branch=master
:target: https://travis-ci.org/ray-project/ray
.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
:target: http://ray.readthedocs.io/en/latest/?badge=latest
|
Ray is a flexible, high-performance distributed execution framework.
View the `documentation`_.
.. _`documentation`: http://ray.readthedocs.io/en/latest/index.html
Description
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
Languages
Python
56.6%
C++
28.8%
Java
8.5%
TypeScript
1.7%
Starlark
1.4%
Other
2.8%