arXiv AI June 11, 2026 By Zhuoran Li, Ling Pan, Jiatai Huang, Longbo Huang

Improving Generalization and Data Efficiency with Diffusion in Offline Multi-agent RL

arXiv:2307. 01472v2 Announce Type: replace Abstract: We present a novel Diffusion Offline Multi-agent Model (DOM2) for offline Multi-Agent Reinforcement Learning (MARL).

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 11

Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies

arXiv:2602. 18291v2 Announce Type: replace Abstract: Online Multi-Agent Reinforcement Learning (MARL) is a prominent framework for efficient agent coordination.

By Zhuoran Li, Hai Zhong, Xun Wang, Qingxin Xia, Lihua Zhang, Longbo Huang

agents diffusion reinforcement-learning multimodal benchmarks

arXiv Machine Learning

Aug 6

State2State: Environment-Derived Mid-Training for LLM Agents

arXiv:2608. 04934v1 Announce Type: cross Abstract: Training LLM agents commonly relies on supervised fine-tuning from expert trajectories or online reinforcement learning over human-specified tasks with handcrafted verifiers.

By Xuanyu Lei, Yiqi Zhu, Chenliang Li, Kaiming Liu, Peng Li, Ming Yan, Jieping Ye, Ya-Qin Zhang, Yang Liu

llms agents reinforcement-learning robotics fine-tuning

arXiv Machine Learning

Jun 5

Training One Model to Master Cross-Level Agentic Actions via Reinforcement Learning

arXiv:2512. 09706v2 Announce Type: replace Abstract: The paradigm of agentic AI is shifting from engineered complex workflows to post-training native models.

By Kaichen He, Zihao Wang, Muyao Li, Anji Liu, Yitao Liang

agents reinforcement-learning robotics fine-tuning benchmarks

arXiv Machine Learning

Jun 4

Enhancing the MADDPG Algorithm for Multi-Agent Learning via Action Inference and Importance Sampling

arXiv:2606. 05021v1 Announce Type: new Abstract: We investigate multi-agent deep reinforcement learning and propose two enhancements to the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm.

By Marc Walden, Jason Liu, Shaashwath Sivakumar, Ryan Liu, Hamza Khan

agents reinforcement-learning benchmarks

arXiv Machine Learning

Jun 16

Diffusion Offline Reinforcement Learning for Fair and Energy-Efficient UAV-Assisted Wireless Networks

arXiv:2606. 16331v1 Announce Type: new Abstract: The integration of generative artificial intelligence with wireless communication and signal processing systems has opened new avenues for intelligent, data-driven decision-making in future 6G networks.

By Eslam Eldeeb, Hirley Alves

diffusion reinforcement-learning efficiency safety

arXiv Machine Learning

Jun 16

FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies

arXiv:2603. 27450v2 Announce Type: replace Abstract: Thanks to their remarkable flexibility, diffusion models and flow models have emerged as promising candidates for policy representation.

By Chenxiao Gao, Edward Chen, Tianyi Chen, Bo Dai

diffusion reinforcement-learning robotics efficiency benchmarks

Related stories

Diffusing to Coordinate: Efficient Online Multi-Agent Diffusion Policies

State2State: Environment-Derived Mid-Training for LLM Agents

Training One Model to Master Cross-Level Agentic Actions via Reinforcement Learning

Enhancing the MADDPG Algorithm for Multi-Agent Learning via Action Inference and Importance Sampling

Diffusion Offline Reinforcement Learning for Fair and Energy-Efficient UAV-Assisted Wireless Networks

FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies