AI Agent - arXivDaily 专题

2603.15054 2026-03-17 cs.AI 89%

Interference-Aware K-Step Reachable Communication in Multi-Agent Reinforcement Learning

考虑干扰的多智能体强化学习中的K步可达通信

Ziyu Cheng, Jinsheng Ren, Zhouxian Jiang, Chenzhihang Li, Rongye Shi, Bin Liang, Jun Yang

机构 * School of Software, Beihang University（软件学院，北航）； School of Artificial Intelligence, Beihang University（人工智能学院，北航）

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

AI总结本文提出IA-KRC框架，通过K步可达协议和干扰预测模块提升多智能体协作效率，克服环境干扰，实现更持久高效的协作。

Comments multi-agent reinforcement learning, communication

2603.13189 2026-03-16 cs.MA cs.AI 89%

LLM Constitutional Multi-Agent Governance

大语言模型宪法多智能体治理

J. de Curtò, I. de Zarzà

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

AI总结本文提出CMAG框架，通过硬约束过滤与软惩罚效用优化，在多智能体群体中平衡合作潜力与操纵风险，实验显示CMAG在保持自主性和完整性的同时提升了合作的伦理得分。

Comments Accepted for publication in 20th International Conference on Agents and Multi-Agent Systems: Technologies and Applications (AMSTA 2026), to appear in Springer Nature proceedings (KES Smart Innovation Systems and Technologies). The final authenticated version will be available online at Springer

2603.05980 2026-03-09 cs.AI 89%

An Interactive Multi-Agent System for Evaluation of New Product Concepts

一个用于新产品概念评估的交互式多智能体系统

Bin Xuan, Ruo Ai, Hakyeon Lee

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

AI总结本文提出基于大型语言模型的多智能体系统，用于自动化评估新产品概念的技术可行性和市场可行性，通过结构化讨论和专业数据微调，验证概念并提升判断准确性。

Comments 46 pages, 3 figures + This paper proposes an LLM-based multi-agent system (MAS) for automated evaluation of new product concepts, incorporating retrieval-augmented generation (RAG) and cross-functional virtual agents to assess technical and market feasibility

2603.00131 2026-03-03 cs.MA cs.AI 89%

Thought Virus: Viral Misalignment via Subliminal Prompting in Multi-Agent Systems

Thought Virus: 通过潜意识提示在多智能体系统中产生病毒性偏差

Moritz Weckbecker, Jonas Müller, Ben Hagag, Michael Mulet

机构 * Carnegie Mellon University（卡内基梅隆大学）

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

AI总结本研究揭示了多智能体系统中通过潜意识提示传播偏见的风险，指出单个智能体的潜意识提示可能影响整个网络的诚实性，提出新的安全攻击向量。

Comments 18 pages, 10 figures, 2 tables. Code available at https://github.com/Multi-Agent-Security-Initiative/thought_virus

2406.13930 2026-02-04 cs.LG 89%

ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning

ME-IGM：最大熵多智能体强化学习中的个体-全局-最大

Wen-Tse Chen, Yuxuan Li, Shiyu Huang, Jiayu Chen, Jeff Schneider

机构 * Carnegie Mellon University（卡内基梅隆大学）； Zhejiang University（浙江大学）； XPeng Inc.（XPeng公司）； The University of Hong Kong（香港大学）； INFIFORCE Intelligent Tech. Co., Ltd.（INFIFORCE智能科技有限公司）

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；autonomous agent(comments,journal_ref)；分类 cs.LG

AI总结 ME-IGM是一种结合最大熵探索与IGM条件的新型多智能体强化学习算法，通过解决局部策略与联合策略不一致问题，提升探索效率和性能。

Comments Published in the Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026)

Journal ref Proc. of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), Paphos, Cyprus, May 25 - 29, 2026, IFAAMAS, 19 pages

2511.23148 2025-12-01 cs.AI 89%

Peer-to-Peer Energy Trading in Dairy Farms using Multi-Agent Reinforcement Learning

基于多智能体强化学习的奶牛场点对点能源交易

Mian Ibad Ali Shah, Marcos Eduardo Cruz Victorio, Maeve Duffy, Enda Barrett, Karl Mason

机构 * School of Computer Science, College of Science and Engineering, University of Galway（Galway大学计算机科学学院）； School of Engineering, College of Science and Engineering, University of Galway（Galway大学工程学院）

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

AI总结本研究利用多智能体强化学习和点对点能源交易，降低奶牛场电力成本和高峰负荷需求，提升能源管理效率。

Comments 51 pages, 7 figures, 11 tables, Preprint of the article published in Applied Energy: Shah, M.I.A., Victorio, M.E.C., Duffy, M., Barrett, E. and Mason, K. (2026). Peer-to-peer energy trading in dairy farms using multi-agent reinforcement learning. Applied Energy, 402, 127041. doi:10.1016/j.apenergy.2025.127041

Journal ref Applied Energy (2026), 402, 127041

2511.03958 2025-11-07 cs.MA cs.CL cs.HC 89%

Multi-Agent Collaborative Framework For Math Problem Generation

Kia Karbasi, Kevin Hong, Mohammad Amin Samadi, Gregory Pottie

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.CL

Comments Published in the Proceedings of the 18th International Conference on Educational Data Mining, 6 pages, 5 figures

Journal ref Kia Karbasi, Kevin Hong, Mohammad Amin Samadi, & Gregory Pottie. (2025). Multi-Agent Collaborative Framework For Math Problem Generation. Proceedings of the 18th International Conference on Educational Data Mining, 613--618

2510.05596 2025-10-08 cs.AI 89%

From Agentification to Self-Evolving Agentic AI for Wireless Networks: Concepts, Approaches, and Future Research Directions

Changyuan Zhao, Ruichen Zhang, Jiacheng Wang, Dusit Niyato, Geng Sun, Xianbin Wang, Shiwen Mao, Abbas Jamalipour

机构 * College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）； College of Computer Science and Technology, Jilin University（计算机科学与技术学院，吉林大学）； Department of Electrical and Computer Engineering, Western University（电气与计算机工程系，西方大学）； Department of Electrical and Computer Engineering, Auburn University（电气与计算机工程系，阿伯茨罕大学）； School of Electrical and Computer Engineering, University of Sydney（电气与计算机工程学院，悉尼大学）

专题命中多智能体：agentic(title,abstract)；agent(abstract)；autonomous agent(abstract)；workflow(abstract)

Comments 7 pages, 4 figures

2305.09349 2025-10-01 cs.AI cs.HC cs.MA 89%

Establishing Shared Query Understanding in an Open Multi-Agent System

Nikolaos Kondylidis, Ilaria Tiddi, Annette ten Teije

机构 * Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；autonomous agent(comments,journal_ref)；分类 cs.AI

Comments 9 pages. International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), London, United Kingdom

Journal ref In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS 23). International Foundation for Autonomous Agents and Multiagent Systems, Richland

2405.16887 2025-09-23 cs.AI cs.MA cs.RO 89%

A Large Language Model-based multi-agent manufacturing system for intelligent shopfloor

Zhen Zhao, Dunbing Tang, Changchun Liu, Liping Wang, Zequn Zhang, Haihua Zhu, Kai Chen, Qingwei Nie, Yuchen Ji

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Journal ref Zhao Z, Tang D, Liu C, et al. A Large language model-based multi-agent manufacturing system for intelligent shopfloors[J]. Advanced Engineering Informatics, 2026, 69: 103888

2506.15672 2025-06-19 cs.AI cs.MA 89%

SwarmAgentic: Towards Fully Automated Agentic System Generation via Swarm Intelligence

Yao Zhang, Chenyang Lin, Shijie Tang, Haokun Chen, Shijie Zhou, Yunpu Ma, Volker Tresp

专题命中多智能体：agentic(title,abstract)；agent(abstract)；autonomous agent(abstract)；planning(abstract)

Comments 41 pages

2506.02739 2025-06-04 cs.AI 89%

Why do AI agents communicate in human language?

Pengcheng Zhou, Yinglun Feng, Halimulati Julaiti, Zhongliang Yang

机构 * Beijing University Of Posts and Telecommunications（北京邮电大学）

专题命中多智能体：AI agent(title,abstract)；agent(abstract)；autonomous agent(abstract)；agentic(abstract)

2506.01463 2025-06-03 cs.MA cs.AI 89%

Agentic AI and Multiagentic: Are We Reinventing the Wheel?

V. Botti

专题命中多智能体：agentic(title,abstract)；agent(abstract)；AI agent(abstract)；autonomous agent(abstract)

2411.04672 2025-05-27 cs.LG cs.MA cs.NI eess.SP 89%

Semantic-Aware Resource Management for C-V2X Platooning via Multi-Agent Reinforcement Learning

Wenjun Zhang, Qiong Wu, Pingyi Fan, Kezhi Wang, Nan Cheng, Wen Chen, Khaled B. Letaief

机构 * School of Internet of Things Engineering, Jiangnan University（江南大学物联网工程学院）； Department of Electronic Engineering, State Key Laboratory of Space Network and Communications, and the Beijing National Research Center for Information Science and Technology, Tsinghua University（清华大学电子工程系、空间网络与通信国家重点实验室及北京信息科学与技术国家研究中心）； Department of Computer Science, Brunel University（布鲁内尔大学计算机科学系）； State Key Laboratory of ISN and the School of Telecommunications Engineering, Xidian University（西安电子科技大学信息与通信系统国家重点实验室及电信工程学院）； Department of Electronic Engineering, Shanghai Jiao Tong University（上海交通大学电子工程系）； Department of Electrical and Computer Engineering, the Hong Kong University of Science and Technology（香港科技大学电子与计算机工程系）

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.LG

Comments This paper has been submitted to IEEE Journal. The source code has been released at:https://github.com/qiongwu86/Semantic-Aware-Resource-Management-for-C-V2X-Platooning-via-Multi-Agent-Reinforcement-Learning

2408.16875 2025-03-03 cs.RO cs.LG 89%

Learning Multi-agent Multi-machine Tending by Mobile Robots

Abdalwhab Abdalwhab, Giovanni Beltrame, Samira Ebrahimi Kahou, David St-Onge

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.LG

Comments 8 pages, 4 figures, Accepted at an AAAI workshop (The Multi-Agent AI in the Real World Workshop)

2303.14061 2025-02-17 cs.AI cs.MA cs.SC 89%

Learning Reward Machines in Cooperative Multi-Agent Tasks

Leo Ardon, Daniel Furelos-Blanco, Alessandra Russo

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments Neuro-symbolic AI for Agent and Multi-Agent Systems Workshop at AAMAS'23

2407.00662 2025-01-09 cs.MA cs.AI 89%

Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach

Nhat-Minh Huynh, Hoang-Giang Cao, I-Chen Wu

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments Accepted at The First Workshop on Game AI Algorithms and Multi-Agent Learning - IJCAI 2024

2412.05838 2024-12-10 cs.AI 89%

A Collaborative Multi-Agent Approach to Retrieval-Augmented Generation Across Diverse Data

Aniruddha Salve, Saba Attar, Mahesh Deshmukh, Sayali Shivpuje, Arnab Mitra Utsab

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments 16 pages, 3 figures. This preprint introduces a multi-agent framework for Retrieval-Augmented Generation (RAG), enhancing Large Language Models (LLMs) for efficient integration of diverse data sources. Relevant for researchers in AI, ML, generative AI, and database systems

2411.10184 2024-11-18 cs.AI 89%

Agentic LLMs in the Supply Chain: Towards Autonomous Multi-Agent Consensus-Seeking

Valeria Jannelli, Stefan Schoepf, Matthias Bickel, Torbjørn Netland, Alexandra Brintrup

专题命中多智能体：agent(title)；agentic(title)；multi-agent(title)；分类 cs.AI

2407.02342 2024-07-03 cs.LG cs.DC cs.MA cs.NI 89%

Optimizing Age of Information in Vehicular Edge Computing with Federated Graph Neural Network Multi-Agent Reinforcement Learning

Wenhua Wang, Qiong Wu, Pingyi Fan, Nan Cheng, Wen Chen, Jiangzhou Wang, Khaled B. Letaief

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.LG

Comments This paper has been submitted to IEEE Journal. The source code has been released at: https://github.com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learning

2405.01839 2024-05-06 cs.AI cs.MA 89%

SocialGFs: Learning Social Gradient Fields for Multi-Agent Reinforcement Learning

Qian Long, Fangwei Zhong, Mingdong Wu, Yizhou Wang, Song-Chun Zhu

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments AAAI 2024 Cooperative Multi-Agent Systems Decision-Making and Learning (CMASDL) Workshop

2309.16263 2024-05-06 cs.GT cs.AI 89%

Cooperation Dynamics in Multi-Agent Systems: Exploring Game-Theoretic Scenarios with Mean-Field Equilibria

Vaigarai Sathi, Sabahat Shaik, Jaswanth Nidamanuri

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments Accepted for MADGames: Multi-Agent Dynamic Games Workshop at IROS 2023, see details at https://iros2023-madgames.f1tenth.org/proceedings.html

2107.04050 2023-05-10 stat.ML cs.LG cs.MA 89%

Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning

Barna Pásztor, Ilija Bogunovic, Andreas Krause

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.LG

Journal ref Pásztor, B., Krause, A., & Bogunovic, I. (2023). Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning. Transactions on Machine Learning Research

2004.08883 2022-02-01 cs.LG cs.MA stat.ML 89%

Variational Policy Propagation for Multi-agent Reinforcement Learning

Chao Qu, Hui Li, Chang Liu, Junwu Xiong, James Zhang, Wei Chu, Weiqiang Wang, Yuan Qi, Le Song

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.LG

Comments The title of previous version was "Intention Propagation for Multi-agent Reinforcement Learning"

2108.13296 2021-08-31 cs.MA cs.AI 89%

Multi-Agent Simulation for AI Behaviour Discovery in Operations Research

Michael Papasimeon, Lyndon Benke

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments 14 pages, 7 figures. To be published in proceedings of the 22nd International Workshop on Multi-Agent-Based Simulation (MABS 2021) at AAMAS 2021. accepted/" target="_blank" rel="noopener">https://mabsworkshop.github.io/accepted/

2010.08615 2021-03-09 eess.SY cs.AI cs.SY math.OC 89%

Decomposability and Parallel Computation of Multi-Agent LQR

Gangshan Jing, He Bai, Jemin George, Aranya Chakrabortty

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments This paper contains proofs of all the theorems in the conference paper "Decomposability and Parallel Computation of Multi-Agent LQR"

2102.01004 2021-02-02 cs.MA cs.AI cs.IT math.IT 89%

Hybrid Information-driven Multi-agent Reinforcement Learning

William A. Dawson, Ruben Glatt, Edward Rusu, Braden C. Soper, Ryan A. Goldhahn

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments Published at Workshop on Challenges and Opportunities for Multi-Agent Reinforcement Learning (COMARL AAAI 2021). This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344. Lawrence Livermore National Security, LLC through the support of LDRD 20-SI-005. LLNL-CONF-816423

1904.04776 2019-07-30 cs.CV cs.LG 89%

Multi-Agent Tensor Fusion for Contextual Trajectory Prediction

Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris Baker, Yibiao Zhao, Yizhou Wang, Ying Nian Wu

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.LG

Comments Presented in CVPR 19: http://openaccess.thecvf.com/content_CVPR_2019/html/Zhao_Multi-Agent_Tensor_Fusion_for_Contextual_Trajectory_Prediction_CVPR_2019_paper.html ; Architecture details available: https://github.com/programmingLearner/MATF-architecture-details

1702.05515 2017-02-21 cs.AI cs.MA cs.RO 89%

Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios

Hang Ma, Sven Koenig, Nora Ayanian, Liron Cohen, Wolfgang Hoenig, T. K. Satish Kumar, Tansel Uras, Hong Xu, Craig Tovey, Guni Sharon

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments In IJCAI-16 Workshop on Multi-Agent Path Finding

1201.5346 2016-11-27 cs.LO cs.AI math.LO 89%

Tableau-based decision procedure for the multi-agent epistemic logic with all coalitional operators for common and distributed knowledge

Mai Ajspur, Valentin Goranko, Dmitry Shkatov

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；分类 cs.AI

Comments Substantially extended and corrected version of arXiv:0902.2125. To appear in: Logic Journal of the IGPL, special issue on Formal Aspects of Multi-Agent Systems

1. 多智能体 14777 篇

Interference-Aware K-Step Reachable Communication in Multi-Agent Reinforcement Learning

LLM Constitutional Multi-Agent Governance

An Interactive Multi-Agent System for Evaluation of New Product Concepts

Thought Virus: Viral Misalignment via Subliminal Prompting in Multi-Agent Systems

ME-IGM: Individual-Global-Max in Maximum Entropy Multi-Agent Reinforcement Learning

Peer-to-Peer Energy Trading in Dairy Farms using Multi-Agent Reinforcement Learning

Multi-Agent Collaborative Framework For Math Problem Generation

From Agentification to Self-Evolving Agentic AI for Wireless Networks: Concepts, Approaches, and Future Research Directions

Establishing Shared Query Understanding in an Open Multi-Agent System

A Large Language Model-based multi-agent manufacturing system for intelligent shopfloor

SwarmAgentic: Towards Fully Automated Agentic System Generation via Swarm Intelligence

Why do AI agents communicate in human language?

Agentic AI and Multiagentic: Are We Reinventing the Wheel?

Semantic-Aware Resource Management for C-V2X Platooning via Multi-Agent Reinforcement Learning

Learning Multi-agent Multi-machine Tending by Mobile Robots

Learning Reward Machines in Cooperative Multi-Agent Tasks

Multi-Agent Training for Pommerman: Curriculum Learning and Population-based Self-Play Approach

A Collaborative Multi-Agent Approach to Retrieval-Augmented Generation Across Diverse Data

Agentic LLMs in the Supply Chain: Towards Autonomous Multi-Agent Consensus-Seeking

Optimizing Age of Information in Vehicular Edge Computing with Federated Graph Neural Network Multi-Agent Reinforcement Learning

SocialGFs: Learning Social Gradient Fields for Multi-Agent Reinforcement Learning

Cooperation Dynamics in Multi-Agent Systems: Exploring Game-Theoretic Scenarios with Mean-Field Equilibria

Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning

Variational Policy Propagation for Multi-agent Reinforcement Learning

Multi-Agent Simulation for AI Behaviour Discovery in Operations Research

Decomposability and Parallel Computation of Multi-Agent LQR

Hybrid Information-driven Multi-agent Reinforcement Learning

Multi-Agent Tensor Fusion for Contextual Trajectory Prediction

Overview: Generalizations of Multi-Agent Path Finding to Real-World Scenarios

Tableau-based decision procedure for the multi-agent epistemic logic with all coalitional operators for common and distributed knowledge