XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

• URL: http://arxiv.org/abs/2312.16248v1
• Date: Mon, 25 Dec 2023 14:45:39 GMT
• Title: XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
• Authors: Wenzhang Liu, Wenzhe Cai, Kun Jiang, Guangran Cheng, Yuanda Wang, Jiawei Wang, Jingyu Cao, Lele Xu, Chaoxu Mu, and Changyin Sun
• Abstract summary: XuanCe is a comprehensive and unified deep reinforcement learning (DRL) library. XuanCe offers a wide range of functionalities, including over 40 classical DRL and multi-agent DRL algorithms. XuanCe is open-source and can be accessed at https://agi-brain.com/agi-brain/xuance.git.
• Score: 18.603206638756056
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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