XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
Wenzhang Liu Wenzhe Cai Kun Jiang Guangran Cheng Yuanda Wang Jiawei Wang Jingyu Cao Lele Xu Chaoxu Mu Changyin Sun
In this paper, we present XuanCe, a comprehensive and unified deep
reinforcement learning (DRL) library designed to be compatible with PyTorch,
TensorFlow, and MindSpore. XuanCe offers a wide range of functionalities,
including over 40 classical DRL and multi-agent DRL algorithms, with the
flexibility to easily incorporate new algorithms and environments. It is a
versatile DRL library that supports CPU, GPU, and Ascend, and can be executed
on various operating systems such as Ubuntu, Windows, MacOS, and EulerOS.
Extensive benchmarks conducted on popular environments including MuJoCo, Atari,
and StarCraftII multi-agent challenge demonstrate the library's impressive
performance. XuanCe is open-source and can be accessed at
https://github.com/agi-brain/xuance.git.