AI Agent

Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding

Shiyue Wang, Haozheng Xu, Yuhan Zhang, Jingran Lin, Changhong Lu, Xiangfeng Wang, Wenhao Li

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

Comments 112 pages, 21 figures, 20 tables. The project website is: https://wangsh1yue.github.io/Where-Paths-Collide

A survey of multi-agent geosimulation methodologies: from ABM to LLM

Virginia Padilla, Jacinto Dávila

机构 * Departamento de Ciencia y Tecnología, Universidad Nacional Experimental de Guayana（科学与技术系，圭亚那国家实验大学） ； CeSiMo, Facultad de Ingeniería, Universidad de los Andes（CeSiMo，工程学院，安第斯大学） 纠错

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

Comments 20 pages, 1 table

Toward the Autonomous AI Doctor: Quantitative Benchmarking of an Autonomous Agentic AI Versus Board-Certified Clinicians in a Real World Setting

Hashim Hayat, Maksim Kudrautsau, Evgeniy Makarov, Vlad Melnichenko, Tim Tsykunou, Piotr Varaksin, Matt Pavelle, Adam Z. Oskowitz

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

EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue Framework

Yao Shi, Rongkeng Liang, Yong Xu

机构 * South China University of Technology（华南理工大学） ； Education Innovation Research Institute of Guangdong（广东教育创新研究院） 纠错

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

Comments Paper URL: https://aclanthology.org/2025.acl-long.1576 ;Presentation Video: https://www.youtube.com/watch?v=j63ooKE50I0

Journal ref Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2025) 32799-32828

DrugMCTS: a drug repurposing framework combining multi-agent, RAG and Monte Carlo Tree Search

Zerui Yang, Yuwei Wan, Siyu Yan, Yudai Matsuda, Tong Xie, Bram Hoex, Linqi Song

机构 * City University of Hong Kong, Hong Kong, PR China（香港城市大学） ； City University of Hong Kong Shenzhen Research Institute, Shenzhen, PR China（香港城市大学深圳研究院） ； The Hong Kong University of Science and Technology (Guangzhou), Guangzhou PR China（香港科学与技术大学（广州）） ； GreenDynamics, Sydney, NSW, Australia（GreenDynamics公司） ； University of New South Wales, Kensington, NSW, Australia（新南威尔士大学） 纠错

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

Distributionally Robust Cascading Risk Quantification in Multi-Agent Rendezvous: Effects of Time Delay and Network Connectivity

Vivek Pandey, Nader Motee

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

Causal-Inspired Multi-Agent Decision-Making via Graph Reinforcement Learning

Jing Wang, Yan Jin, Fei Ding, Chongfeng Wei

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

Decentralized Uncertainty-Aware Multi-Agent Collision Avoidance with Model Predictive Path Integral

Stepan Dergachev, Konstantin Yakovlev

机构 * FRC CSC RAS（俄罗斯科学院应用数学与控制论研究所） ； HSE University（俄罗斯高等经济大学） ； AIRI（人工智能研究所） 纠错

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

Comments This is a pre-print of the paper accepted to IROS2025. The manuscript includes 8 pages, 4 figures, and 1 table. A supplementary video is available at https://youtu.be/_D4zDYJ4KCk Updated version: added link to source code in the abstract; updated experimental results description in Section VI.A; updated author affiliation and funding information; minor typo corrections

SDHN: Skewness-Driven Hypergraph Networks for Enhanced Localized Multi-Robot Coordination

Delin Zhao, Yanbo Shan, Chang Liu, Shenghang Lin, Yingxin Shou, Bin Xu

机构 * School of Automation, Northwestern Polytechnical University, Xi'an, 710072, China（西北工业大学自动化学院） ； School of Automation, Southeast University, Nanjing, 210096, China（东南大学自动化学院） 纠错

专题命中 多智能体 ：agent(abstract)；multi-agent(abstract)

Exploiting Local Observations for Robust Robot Learning

Wenshuai Zhao, Eetu-Aleksi Rantala, Sahar Salimpour, Zhiyuan Li, Joni Pajarinen, Jorge Peña Queralta

专题命中 多智能体 ：agent(abstract)；multi-agent(abstract)

Comments 8 pages, 8 figures