New Features

  • Add the first open-source industrial evolution strategy framework EvoKit
  • Support Multi-Agent RL algorithms, including MADDPG
  • Support multiple GPU training, provide a demonstration of DQN with multi GPU
  • Add SOTA algorithms of continuous control problems, TD3 and SAC
  • Add the champion model and training method of NeurIPS 2019 reinforcement learning competition
  • Compatible with Windows

项目简介

A high-performance distributed training framework for Reinforcement Learning

发行版本 5

PARL 1.3

全部发行版

贡献者 23

全部贡献者

开发语言

  • Python 82.6 %
  • C++ 10.3 %
  • JavaScript 3.1 %
  • Shell 1.4 %
  • CMake 1.2 %