mlsanityData to 7 Oct 2026

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

arXiv 2312.16248 ↗First posted 25 Dec 2023cs.LG cs.AI cs.DLcited by 5

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Abstract (arXiv)

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.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 20 of its 28 references that are in the map. First posted on arXiv 25 Dec 2023.

Builds on

20 of 28 references.

References · 20

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2017Proximal Policy Optimization Algorithmscited by 14,441
  3. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,635
  4. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,302
  5. 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 903
  6. 2017Value-Decomposition Networks For Cooperative Multi-Agent Learningcited by 490
  7. 2020Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learningcited by 475
  8. 2017StarCraft II: A New Challenge for Reinforcement Learningcited by 268
  9. 2019Google Research Football: A Novel Reinforcement Learning Environmentcited by 257
  10. 2021Tianshou: a Highly Modularized Deep Reinforcement Learning Librarycited by 139
  11. 2018Dopamine: A Research Framework for Deep Reinforcement Learningcited by 121
  12. 2021d3rlpy: An Offline Deep Reinforcement Learning Librarycited by 84
8 more
  1. 2017MAgent: A Many-Agent Reinforcement Learning Platform for Artificial Collective Intelligencecited by 69
  2. 2021FinRL: Deep Reinforcement Learning Framework to Automate Trading in Quantitative Financecited by 57
  3. 2019ChainerRL: A Deep Reinforcement Learning Librarycited by 51
  4. 2020MushroomRL: Simplifying Reinforcement Learning Researchcited by 50
  5. 2020OR-Gym: A Reinforcement Learning Library for Operations Research Problemscited by 50
  6. 2020Value-Decomposition Multi-Agent Actor-Criticscited by 47
  7. 2022skrl: Modular and Flexible Library for Reinforcement Learningcited by 35
  8. 2020Tonic: A Deep Reinforcement Learning Library for Fast Prototyping and Benchmarkingcited by 18

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 3.

5 papers.

  1. 2026Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Frameworkcited by 1
  2. 2024Conceptual Belief-Informed Reinforcement Learningcited by 0
  3. 2025Agent2: An Agent-Generates-Agent Framework for Reinforcement Learning Automationcited by 0
  4. 2026MOSAIC: A Universal Agent-Level Interface for Cross-Paradigm Agent Mixing and Human-AI Collaborationcited by 0
  5. 2026MARS-RA: Rank Aggregation for Credit Assignment via Multimodal Comparisons in Embodied Multi-Agent Cooperationcited by 0