AI Agent

SurgRAW: Multi-Agent Workflow with Chain of Thought Reasoning for Robotic Surgical Video Analysis

SurgRAW：基于链式推理的多智能体工作流用于机器人手术视频分析

Chang Han Low, Ziyue Wang, Tianyi Zhang, Zhu Zhuo, Zhitao Zeng, Evangelos B. Mazomenos, Yueming Jin

机构 * National University of Singapore（国立新加坡大学） ； Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR)（生物信息研究所（BII），科技研究局（A*STAR）） ； Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) and the Department of Medical Physics and Biomedical Engineering, University College London（Wellcome/EPSRC介入与外科科学中心（WEISS）及伦敦大学学院医学物理与生物医学工程系） 纠错

专题命中 规划决策 ：workflow(title,abstract)；agent(title)；multi-agent(title)；agentic(abstract)

AI总结 SurgRAW通过基于链式推理的多智能体工作流，在机器人手术视频分析中实现零样本多任务推理，提升准确性和临床相关性。

Journal ref IEEE Robotics and Automation Letters, 2026, pp. 1-8

Learning to Deliberate: Meta-policy Collaboration for Agentic LLMs with Multi-agent Reinforcement Learning

学习 deliberation：基于多智能体强化学习的元策略协作用于代理语言模型

Wei Yang, Jesse Thomason

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；agentic(title)；分类 cs.AI

AI总结 本文提出元策略推理框架MPDF，结合SoftRankPO算法，通过学习动态推理策略提升多智能体LLM在复杂推理任务中的性能。

A Knowledge-Graph Translation Layer for Mission-Aware Multi-Agent Path Planning in Spatiotemporal Dynamics

Edward Holmberg, Elias Ioup, Mahdi Abdelguerfi

机构 * Cannizaro-Livingston Gulf States Center for Environmental Informatics（坎尼扎罗-利文斯顿海湾州环境信息中心） ； Center for Geospatial Sciences Naval Research Laboratory（地理空间科学中心海军研究实验室） 纠错

专题命中 规划决策 ：agent(title,abstract)；planning(title)；multi-agent(title)；autonomous agent(abstract)

Comments 10 pages, 10 figures, conference submission

Towards Urban Planing AI Agent in the Age of Agentic AI

Rui Liu, Tao Zhe, Zhong-Ren Peng, Necati Catbas, Xinyue Ye, Dongjie Wang, Yanjie Fu

机构 * University of Kansas（堪萨斯大学） ； University of Florida（佛罗里达大学） ； University of Central Florida（中央佛罗里达大学） ； University of Alabama（阿拉巴马大学） ； Arizona State University（亚利桑那州立大学） 纠错

专题命中 规划决策 ：agentic(title,abstract)；agent(title)；AI agent(title)；planning(abstract)

Comments this more comprehensive version is under reviewed in ACM SIGKDD exploration

AI-Driven Multi-Agent Vehicular Planning for Battery Efficiency and QoS in 6G Smart Cities

Rohin Gillgallon, Giacomo Bergami, Reham Almutairi, Graham Morgan

机构 * School of Computing, Newcastle University（计算学院，新萨克勒大学） ； Computer Science Department, University of Hafr Albatin（计算机科学系，哈夫阿尔巴丁大学） 纠错

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)；分类 cs.AI

Comments 16 pages, 2 figures, 2 tables, 2 algorithms

PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks

Matthew Chang, Gunjan Chhablani, Alexander Clegg, Mikael Dallaire Cote, Ruta Desai, Michal Hlavac, Vladimir Karashchuk, Jacob Krantz, Roozbeh Mottaghi, Priyam Parashar, Siddharth Patki, Ishita Prasad, Xavier Puig, Akshara Rai, Ram Ramrakhya, Daniel Tran, Joanne Truong, John M. Turner, Eric Undersander, Tsung-Yen Yang

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)；分类 cs.AI

Comments Alphabetical author order

Factorization of Multi-Agent Sampling-Based Motion Planning

Alessandro Zanardi, Pietro Zullo, Andrea Censi, Emilio Frazzoli

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)；分类 cs.AI

Comments under review

Fault-Tolerant Offline Multi-Agent Path Planning

Keisuke Okumura, Sébastien Tixeuil

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)；分类 cs.AI

Comments to be presented at AAAI-23

Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing

Liang Wang, Kezhi Wang, Cunhua Pan, Wei Xu, Nauman Aslam, Lajos Hanzo

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(title)；分类 cs.LG

Comments Accepted by IEEE Transactions on Cognitive Communications and Networking

A Coordinated MDP Approach to Multi-Agent Planning for Resource Allocation, with Applications to Healthcare

Hadi Hosseini, Jesse Hoey, Robin Cohen

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)；分类 cs.AI

Comments 6 pages

A Framework for Sequential Planning in Multi-Agent Settings

P. Doshi, P. J. Gmytrasiewicz

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(title)；分类 cs.AI

Journal ref Journal Of Artificial Intelligence Research, Volume 24, pages 49-79, 2005

From What to Why: A Multi-Agent System for Evidence-based Chemical Reaction Condition Reasoning

从何到为何：一个用于基于证据的化学反应条件推理的多智能体系统

Cheng Yang, Jiaxuan Lu, Haiyuan Wan, Junchi Yu, Feiwei Qin

机构 * Hangzhou Dianzi University（杭州电子科技大学） ； Shanghai Artificial Intelligence Laboratory（上海人工智能实验室） ； Tsinghua University（清华大学） ； University of Oxford（牛津大学） 纠错

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(abstract)；agentic(abstract)

AI总结 本文提出ChemMAS多智能体系统，通过机制 grounding、多通道回忆、约束感知辩论和理由聚合，提升化学反应条件推荐的可解释性，实验表明其在准确率和可解释性上优于现有方法。

Comments Accepted by ICLR 2026

Comparative Analysis of AI Agent Architectures for Entity Relationship Classification

面向实体关系分类的AI代理架构比较分析

Maryam Berijanian, Kuldeep Singh, Amin Sehati

机构 * Michigan State University（密歇根州立大学） 纠错

专题命中 规划决策 ：agent(title,abstract)；AI agent(title,abstract)；agentic(abstract)；multi-agent(abstract)

AI总结 本文比较了三种基于大语言模型的AI代理架构在实体关系分类中的性能，发现多代理协作优于少样本提示方法，接近微调模型性能。

Journal ref Proceedings of the 18th International Conference on Agents and Artificial Intelligence, Volume 1: ICAART, 2026

DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints

DeepPlanning: 用可验证约束基准测试长周期代理规划

Yinger Zhang, Shutong Jiang, Renhao Li, Jianhong Tu, Yang Su, Lianghao Deng, Xudong Guo, Chenxu Lv, Junyang Lin

机构 * Alibaba Group（阿里巴巴集团） 纠错

专题命中 规划决策 ：planning(title,abstract)；agentic(title,abstract)；agent(abstract)；tool use(abstract)

AI总结 DeepPlanning是一个针对长周期代理规划的基准测试，通过多日旅行和多产品购物任务，评估代理在全局约束优化和局部约束推理中的能力。

A Self-Evolving AI Agent System for Climate Science

Zijie Guo, Jiong Wang, Fenghua Ling, Wangxu Wei, Xiaoyu Yue, Zhe Jiang, Wanghan Xu, Jing-Jia Luo, Lijing Cheng, Yoo-Geun Ham, Fengfei Song, Pierre Gentine, Toshio Yamagata, Ben Fei, Wenlong Zhang, Xinyu Gu, Chao Li, Yaqiang Wang, Tao Chen, Wanli Ouyang, Bowen Zhou, Lei Bai

专题命中 规划决策 ：agent(title,abstract)；AI agent(title,abstract)；planning(abstract)；workflow(abstract)

SAFEFLOW: A Principled Protocol for Trustworthy and Transactional Autonomous Agent Systems

Peiran Li, Xinkai Zou, Zhuohang Wu, Ruifeng Li, Shuo Xing, Hanwen Zheng, Zhikai Hu, Yuping Wang, Haoxi Li, Qin Yuan, Yingmo Zhang, Zhengzhong Tu

专题命中 规划决策 ：agent(title,abstract)；autonomous agent(title,abstract)；tool use(abstract)；multi-agent(abstract)

Comments Former versions either contain unrelated content or cannot be properly converted to PDF

Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories

Nanxu Gong, Sixun Dong, Haoyue Bai, Xinyuan Wang, Wangyang Ying, Yanjie Fu

机构 * Arizona State University（亚利桑那州立大学） 纠错

专题命中 规划决策 ：planning(title,abstract)；agentic(title,abstract)；agent(abstract)；multi-agent(abstract)

POLARIS: Typed Planning and Governed Execution for Agentic AI in Back-Office Automation

POLARIS：面向后台自动化代理AI的类型化规划与受控执行

Zahra Moslemi, Keerthi Koneru, Yen-Ting Lee, Sheethal Kumar, Ramesh Radhakrishnan

机构 * University of California, Irvine（加州大学尔湾分校） ； Center for Advanced AI, Accenture（Accenture高级人工智能中心） ； University of California, San Diego（加州大学圣地亚哥分校） 纠错

专题命中 规划决策 ：agentic(title,abstract)；planning(title,abstract)；agent(abstract)；multi-agent(abstract)

AI总结 POLARIS通过类型化规划和受控执行框架，提升后台自动化中代理AI的政策一致性与可预测性，实现高精度任务处理与审计追踪。

Comments Workshop on Agentic AI Benchmarks and Applications for Enterprise Tasks: AAAI 2026

RS-Agent: Automating Remote Sensing Tasks through Intelligent Agent

RS-Agent：通过智能代理实现遥感任务自动化

Wenjia Xu, Zijian Yu, Boyang Mu, Jiuniu Wang, Zhiwei Wei, Mugen Peng

机构 * State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China（网络与交换技术国家重点实验室，北京邮电大学，中国） ； City University of HongKong, Hong Kong 999077, China（香港城市大学，中国） ； School of Geographic Sciences, Hunan Normal University, Changsha 410081, China（地理科学学院，湖南师范大学，中国） 纠错

专题命中 规划决策 ：agent(title,title_cn)；planning(abstract)

AI总结 针对多模态大语言模型在遥感任务中的局限，提出RS-Agent智能代理，通过结构化任务规划等连接用户意图与遥感流程，含四个组件及两种方法，实验显示其在多任务中显著优于现有模型，证明结合两者用于智能地理空间分析的价值。

Simulating Cooperative Prosocial Behavior with Multi-Agent LLMs: Evidence and Mechanisms for AI Agents to Inform Policy Decisions

Karthik Sreedhar, Alice Cai, Jenny Ma, Jeffrey V. Nickerson, Lydia B. Chilton

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；AI agent(title)

Optimizing UAV-UGV Coalition Operations: A Hybrid Clustering and Multi-Agent Reinforcement Learning Approach for Path Planning in Obstructed Environment

Shamyo Brotee, Farhan Kabir, Md. Abdur Razzaque, Palash Roy, Md. Mamun-Or-Rashid, Md. Rafiul Hassan, Mohammad Mehedi Hassan

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(title)

GAMEOPT: Optimal Real-time Multi-Agent Planning and Control for Dynamic Intersections

Nilesh Suriyarachchi, Rohan Chandra, John S. Baras, Dinesh Manocha

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)

Comments Submitted to ITSC 2022

SMA-NBO: A Sequential Multi-Agent Planning with Nominal Belief-State Optimization in Target Tracking

Tianqi Li, Lucas W. Krakow, Swaminathan Gopalswamy

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(title)

Scalable Planning in Multi-Agent MDPs

Dinuka Sahabandu, Luyao Niu, Andrew Clark, Radha Poovendran

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(title)

Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances

Jingkai Chen, Jiaoyang Li, Chuchu Fan, Brian Williams

专题命中 规划决策 ：agent(title,abstract)；multi-agent(title,abstract)；planning(title)

Comments Accepted at AAAI2021. 9 pages, 5 figures, 1 table

Multi-agent Gaussian Process Motion Planning via Probabilistic Inference

Luka Petrović, Ivan Marković, Marija Seder

专题命中 规划决策 ：agent(title,abstract)；planning(title,abstract)；multi-agent(title)

Comments Accepted for oral presentation at 12th IFAC Symposium on Robot Control (SYROCO 2018)

Agent-BRACE: Decoupling Beliefs from Actions in Long-Horizon Tasks via Verbalized State Uncertainty

Agent-BRACE: 通过 verbalized 状态不确定性解耦信念与行动以应对长 horizon 任务

Joykirat Singh, Zaid Khan, Archiki Prasad, Justin Chih-Yao Chen, Akshay Nambi, Hyunji Lee, Elias Stengel-Eskin, Mohit Bansal

机构 * UNC Chapel Hill（北卡罗来纳大学教堂山分校） ； The University of Texas at Austin（德克萨斯大学奥斯汀分校） ； Microsoft Research（微软研究院） 纠错

专题命中 规划决策 ：agent(title,title_cn)；分类 cs.AI、cs.CL

AI总结 Agent-BRACE 通过解耦信念状态模型与策略模型，利用强化学习优化，在长 horizon 部分可观测任务中提升性能，实现上下文窗口恒定且任务相关信息保留。

Comments Code: https://github.com/joykirat18/Agent-BRACE

Agentic Reasoning for Large Language Models

大语言模型的代理推理

Tianxin Wei, Ting-Wei Li, Zhining Liu, Xuying Ning, Ze Yang, Jiaru Zou, Zhichen Zeng, Ruizhong Qiu, Xiao Lin, Dongqi Fu, Zihao Li, Mengting Ai, Duo Zhou, Wenxuan Bao, Yunzhe Li, Gaotang Li, Cheng Qian, Yu Wang, Xiangru Tang, Yin Xiao, Liri Fang, Hui Liu, Xianfeng Tang, Yuji Zhang, Chi Wang, Jiaxuan You, Heng Ji, Hanghang Tong, Jingrui He

专题命中 规划决策 ：agentic(title,abstract)；agent(abstract)；autonomous agent(abstract)；tool use(abstract)

AI总结 本文探讨了大语言模型在开放和动态环境中的代理推理方法，通过三个层次的框架提升单体、自我进化和集体多代理推理能力，并提出了未来研究方向。

Comments Project: https://github.com/weitianxin/Awesome-Agentic-Reasoning

Personalization as Inverse Planning: Learning Latent Design Intents for Agentic Slide Generation via Structural Denoising

个性化作为逆向规划：通过结构去噪学习智能幻灯片生成的潜在设计意图

Tianci Liu, Zihan Dong, Linjun Zhang, Haoyu Wang, Jing Gao, Emre Kiciman, Ranveer Chandra, Wei-Ting Chen

机构 * Purdue University（普渡大学） ； Rutgers University（罗格斯大学） ； University at Albany（奥尔巴尼大学） ； Microsoft（微软） 纠错

专题命中 规划决策 ：planning(title,abstract)；agentic(title)；agent(abstract)；AI agent(abstract)

AI总结 提出SPIRE框架，将页面级幻灯片个性化视为逆向规划问题，通过结构去噪和强化学习协作学习潜在设计意图，无需预设模板或用户详细指令。

Comments ECCV 2026

LAVE: Latent Visual Evidence-Enhanced Planning for Video Tool-use Agents

LAVE：面向视频工具使用智能体的隐式视觉证据增强规划

Zijian Wang, Junnan Zhu, Rongzhen Li, Xiao Liu, Guohui Xiang, Quan Lu, Lijia Liu, Yining Wang, Jiang Zhong, Kaiwen Wei

专题命中 规划决策 ：planning(title,abstract)；tool-use(title,abstract)；agent(abstract)；分类 cs.LG

AI总结 针对视频工具使用智能体的工具观测瓶颈，提出无训练框架LAVE，通过双通道观测接口复用隐式视觉证据，在三个基准数据集上提升了智能体性能，Video-MME得分较最强基线提高3.76分。

Comments 16 pages, 6 figures, 9 tables. Includes appendix