AI Agent - arXivDaily 专题

1803.02018 2018-03-07 cs.AI 89%

Intent-aware Multi-agent Reinforcement Learning

Siyuan Qi, Song-Chun Zhu

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

Comments ICRA 2018

1710.06525 2017-10-19 cs.AI cs.MA 89%

Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems

Trong Nghia Hoang, Yuchen Xiao, Kavinayan Sivakumar, Christopher Amato, Jonathan How

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

1408.5891 2014-08-27 cs.SE cs.MA 89%

Integration of Heterogeneous Systems as Multi-Agent Systems

Ammar Lahlouhi

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

Comments Journal of Systems Integration, Vol 5, No 3 (2014)

1302.2828 2013-02-13 cs.RO cs.AI cs.MA 89%

Multi-agent RRT*: Sampling-based Cooperative Pathfinding (Extended Abstract)

Michal Čáp, Peter Novák, Jiří Vokřínek, Michal Pěchouček

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

Comments To appear at AAMAS 2013

2502.00558 2026-05-20 cs.MA 89%

Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication

异步协作多智能体强化学习与有限通信

Sydney Dolan, Siddharth Nayak, Jasmine Jerry Aloor, Hamsa Balakrishnan

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；autonomous agent(abstract,journal_ref)

AI总结本研究提出了一种异步多智能体强化学习框架AsynCoMARL，通过图Transformer学习动态图中的通信协议，在通信受限环境下实现高效协作，相比传统同步方法，减少26%的通信量同时保持相近的成功率和碰撞率。

Journal ref Proceedings of the 2025 International Conference on Autonomous Agents and Multiagent Systems

2603.26635 2026-03-30 cs.MA 89%

Deception and Communication in Autonomous Multi-Agent Systems: An Experimental Study with Among Us

自主多智能体系统中的欺骗与交流：以Among Us为例的实证研究

Maria Milkowski, Tim Weninger

专题命中多智能体：agent(title,abstract)；multi-agent(title,abstract)；autonomous agent(abstract,journal_ref)

AI总结本文通过Among Us游戏研究自主智能体的欺骗与交流行为，发现智能体主要使用指示性语言，伪装者倾向使用解释和否认等行为，欺骗多表现为 equivocation 而非直接谎言，揭示了自主交流中真理与效用之间的根本矛盾。

Comments 8 pages + references, 9 figures. Accepted at AAMAS 2026

Journal ref Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2026), IFAAMAS, 2026

2502.06060 2025-02-11 cs.AI cs.CL cs.LG cs.MA 89%

Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning

Bidipta Sarkar, Warren Xia, C. Karen Liu, Dorsa Sadigh

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

Comments 14 pages, 5 figures, 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025)

2608.20341 2026-08-24 cs.AI cs.SE 新提交 89%

SDAD: Spec-Driven Agentic Development for the AI-Native SDLC

SDAD：面向AI原生软件开发生命周期的规范驱动智能体开发

Vu Hung Nguyen, Thanh Nguyen

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

AI总结该研究提出规范驱动智能体开发（SDAD）模型，对比传统敏捷开发，扩展团队角色、量化治理等，论证智能体开发需将工程规范转移至上游规范环节。

2608.05107 2026-08-06 cs.AI cs.MA cs.SE 新提交 89%

CoPlan: A Trustworthy Co-Intelligence Interface for Care Planning through Role-Based Contestable Argument Graphs

CoPlan：一种基于角色可争议论证图的可信协同智能照护规划界面

Hung Truong Thanh Nguyen, Hélène Fournier, Piper Jackson, Makoto Itoh, Shannon Freeman, Rene Richard, Hung Cao

机构 * University of New Brunswick（新不伦瑞克大学）； National Research Council Canada（加拿大国家研究委员会）； Thompson Rivers University（汤普森河大学）； ISB Corporation（ISB公司）； University of Northern British Columbia（北英属哥伦比亚大学）

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

AI总结本研究提出CoPlan界面，通过多智能体工作流结合协同智能与可争议性，实现人机协同照护规划，保留人类自主性与临床问责制，已在就地养老场景中验证其有效性。

Comments Accepted at the 2026 International Conference on Next Generation AI Systems (NGEN-AI 2026)

2607.29405 2026-08-03 cs.AI cs.MA cs.SE 新提交 89%

Beyond Component Testing: Validating Agentic AI Systems

超越组件测试：验证智能体AI系统

Fabio Orazio Mirto, Luca D'Agati, Giuseppe Tricomi, Stefano Silvestri, Francesco Longo, Antonio Puliafito, Giovanni Merlino

机构 * University of Messina（墨西拿大学）

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

AI总结该综述综合257篇相关文献，构建五维分类法分析智能体AI系统验证问题，指出现有方法的缺口，提出面向生命周期的研究议程，主张需在上下文中验证智能体轨迹以实现可信部署。

Comments 61 pages, 3 figures, to be submitted to Springer Artificial Intelligence Review

2411.04867 2025-08-28 cs.AI cs.LG 89%

Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning

Satchit Chatterji, Erman Acar

机构 * IvI \& ILLC, University of Amsterdam

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

Comments Accepted to the 28th European Conference on Artificial Intelligence (ECAI 2025) --- 21 pages, 15 figures, Earlier title: "Analyzing Probabilistic Logic Driven Safety in Multi-Agent Reinforcement Learning"; (changed for specificity and clarity)

2506.20039 2025-06-26 cs.MA cs.AI cs.GT cs.LG 89%

Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning

Koorosh Moslemi, Chi-Guhn Lee

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

Comments Accepted to the 2nd Coordination and Cooperation in Multi-Agent Reinforcement Learning (CoCoMARL) Workshop at RLC 2025

2301.08278 2025-03-18 cs.MA cs.AI cs.LG 89%

Investigating the Impact of Direct Punishment on the Emergence of Cooperation in Multi-Agent Reinforcement Learning Systems

Nayana Dasgupta, Mirco Musolesi

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

Comments 50 pages, 19 figures

Journal ref Auton Agent Multi-Agent Syst 39, 19 (2025)

2502.07165 2025-02-12 cs.CL cs.AI 89%

Don't Just Demo, Teach Me the Principles: A Principle-Based Multi-Agent Prompting Strategy for Text Classification

Peipei Wei, Dimitris Dimitriadis, Yan Xu, Mingwei Shen

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

Comments To be published in AAAI 2025 Workshop on Advancing LLM-Based Multi-Agent Collaboration

2405.00839 2024-10-22 cs.LG cs.AI cs.DC cs.MA cs.PF 89%

Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning

Seyed Mahmoud Sajjadi Mohammadabadi, Lei Yang, Feng Yan, Junshan Zhang

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

Comments This paper has been accepted for presentation at ICDCS (44th IEEE International Conference on Distributed Computing Systems). Keywords: decentralized multi-agent learning, federated learning, edge computing, heterogeneous agents, workload balancing, and communication-efficient training )

Journal ref 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS)

2401.09886 2024-06-06 cs.LG cs.AI 89%

Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network

Qiong Wu, Wenhua Wang, Pingyi Fan, Qiang Fan, Huiling Zhu, Khaled B. Letaief

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

Comments This paper has been submitted to IEEE TNSM. The source code has been released at: https://github.com/qiongwu86/Edge-Caching-Based-on-Multi-Agent-Deep-Reinforcement-Learning-and-Federated-Learning

2309.10007 2023-10-03 cs.RO cs.AI cs.LG cs.MA 89%

Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles using AutoDRIVE Ecosystem

Tanmay Vilas Samak, Chinmay Vilas Samak, Venkat Krovi

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

Comments Accepted as Multi-Agent Dynamic Games (MAD-Games) Workshop Paper at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023

2303.16641 2023-03-30 cs.MA cs.AI cs.LG cs.RO cs.SY eess.SY 89%

A Hierarchical Game-Theoretic Decision-Making for Cooperative Multi-Agent Systems Under the Presence of Adversarial Agents

Qin Yang, Ramviyas Parasuraman

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

Comments This paper is accepted by the ACM Symposium on Applied Computing (SAC) 2023 Technical Track on Intelligent Robotics and Multi-Agent Systems (IRMAS)

2205.15716 2022-10-17 cs.LG cs.AI cs.MA 89%

Multi-Agent Learning of Numerical Methods for Hyperbolic PDEs with Factored Dec-MDP

Yiwei Fu, Dheeraj S. K. Kapilavai, Elliot Way

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

Comments Submitted to 20th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2022)

2209.14239 2022-09-29 cs.MA cs.AI cs.LG 89%

How to solve a classification problem using a cooperative tiling Multi-Agent System?

Thibault Fourez, Nicolas Verstaevel, Frédéric Migeon, Frédéric Schettini, Frédéric Amblard

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

Comments 20th International Conference on Practical Applications of Agents and Multi-Agent Systems, Jul 2022, L'Aquila, Italy. arXiv admin note: substantial text overlap with arXiv:2209.06824

2110.08642 2021-12-21 cs.LG cs.AI cs.MA 89%

Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning

Yuchen Xiao, Xueguang Lyu, Christopher Amato

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

Journal ref IEEE The 3rd International Symposium on Multi-Robot and Multi-Agent Systems (MRS), 2021

2106.06828 2021-06-15 cs.MA cs.AI cs.LG 89%

A Game-Theoretic Approach to Multi-Agent Trust Region Optimization

Ying Wen, Hui Chen, Yaodong Yang, Zheng Tian, Minne Li, Xu Chen, Jun Wang

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

Comments A Multi-Agent Trust Region Learning (MATRL) algorithm that augments the single-agent trust region policy optimization with a weak stable fixed point approximated by the policy-space meta-game

2002.08878 2020-10-28 cs.MA cs.CL cs.LG 89%

Multi-Agent Reinforcement Learning as a Computational Tool for Language Evolution Research: Historical Context and Future Challenges

Clément Moulin-Frier, Pierre-Yves Oudeyer

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

Journal ref Challenges and Opportunities for Multi-Agent Reinforcement Learning (COMARL AAAI 2020-2021), AAAI Spring Symposium Series, Stanford University, Palo Alto, California, USA

1811.07029 2018-11-20 cs.LG cs.AI cs.MA stat.ML 89%

Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG

Hangyu Mao, Zhengchao Zhang, Zhen Xiao, Zhibo Gong

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

Comments Attention-based Multi-agent DDPG. Experimental results show that it not only outperforms the state-of-the-art RL-based methods and rule-based methods by a large margin, but also achieves better performance in terms of scalability and robustness

1706.03235 2017-10-31 cs.AI cs.LG 89%

ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning

Hangyu Mao, Zhibo Gong, Yan Ni, Zhen Xiao

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

Comments V3 of original submission. Actor-Critic Method for Multi-agent Learning-to-Communicate based on Deep Reinforcement Learning, It is suitable for both continuous and discrete action space environments

1708.02361 2017-08-09 cs.MA cs.AI cs.SE nlin.AO nlin.CG 89%

Verification & Validation of Agent Based Simulations using the VOMAS (Virtual Overlay Multi-agent System) approach

Muaz A. Niazi, Amir Hussain, Mario Kolberg

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

Comments 7 pages, 5 figures, cite as Muaz Niazi, Amir Hussain and Mario Kolberg , Verification and Validation of Agent-Based Simulation using the VOMAS approach, Proceedings of the Third Workshop on Multi-Agent Systems and Simulation'09 (MASS '09), as part of MALLOW 09, Sep 7-11, 2009, Torino, Italy

2404.01131 2024-04-16 cs.MA cs.AI 89%

GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems

Ashish Rana, Michael Oesterle, Jannik Brinkmann

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

Comments Extended Abstract accepted in the 23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2024)

2210.17540 2022-11-01 cs.LG cs.MA 89%

Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning

Jennifer She, Jayesh K. Gupta, Mykel J. Kochenderfer

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

Comments Full version of the Extended Abstract accepted at the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2022

2102.08370 2022-10-18 cs.MA cs.AI 89%

Quantifying the effects of environment and population diversity in multi-agent reinforcement learning

Kevin R. McKee, Joel Z. Leibo, Charlie Beattie, Richard Everett

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

Comments Accepted at Autonomous Agents and Multi-Agent Systems

2111.13145 2021-11-29 cs.AI cs.MA 89%

Unravelling multi-agent ranked delegations

Rachael Colley, Umberto Grandi, Arianna Novaro

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

Comments 48 pages, 5 Tables, 3 Figures, to be published in the Journal of Autonomous Agents and Multi-Agent Systems

1. 多智能体 14880 篇

Intent-aware Multi-agent Reinforcement Learning

Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous Multi-Agent Systems

Integration of Heterogeneous Systems as Multi-Agent Systems

Multi-agent RRT*: Sampling-based Cooperative Pathfinding (Extended Abstract)

Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication

Deception and Communication in Autonomous Multi-Agent Systems: An Experimental Study with Among Us

Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning

SDAD: Spec-Driven Agentic Development for the AI-Native SDLC

CoPlan: A Trustworthy Co-Intelligence Interface for Care Planning through Role-Based Contestable Argument Graphs

Beyond Component Testing: Validating Agentic AI Systems

Think Smart, Act SMARL! Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning

Learning Bilateral Team Formation in Cooperative Multi-Agent Reinforcement Learning

Investigating the Impact of Direct Punishment on the Emergence of Cooperation in Multi-Agent Reinforcement Learning Systems

Don't Just Demo, Teach Me the Principles: A Principle-Based Multi-Agent Prompting Strategy for Text Classification

Communication-Efficient Training Workload Balancing for Decentralized Multi-Agent Learning

Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Network

Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles using AutoDRIVE Ecosystem

A Hierarchical Game-Theoretic Decision-Making for Cooperative Multi-Agent Systems Under the Presence of Adversarial Agents

Multi-Agent Learning of Numerical Methods for Hyperbolic PDEs with Factored Dec-MDP

How to solve a classification problem using a cooperative tiling Multi-Agent System?

Local Advantage Actor-Critic for Robust Multi-Agent Deep Reinforcement Learning

A Game-Theoretic Approach to Multi-Agent Trust Region Optimization

Multi-Agent Reinforcement Learning as a Computational Tool for Language Evolution Research: Historical Context and Future Challenges

Modelling the Dynamic Joint Policy of Teammates with Attention Multi-agent DDPG

ACCNet: Actor-Coordinator-Critic Net for "Learning-to-Communicate" with Deep Multi-agent Reinforcement Learning

Verification & Validation of Agent Based Simulations using the VOMAS (Virtual Overlay Multi-agent System) approach

GOV-REK: Governed Reward Engineering Kernels for Designing Robust Multi-Agent Reinforcement Learning Systems

Agent-Time Attention for Sparse Rewards Multi-Agent Reinforcement Learning

Quantifying the effects of environment and population diversity in multi-agent reinforcement learning

Unravelling multi-agent ranked delegations