Multi-Agent System Optimization

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10 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Optimal and Scalable MAPF via Multi-Marginal Optimal Transport and Schrödinger Bridges
May 11, 2026Usman A. Khan, Joseph W. DurhamMulti-Agent System Optimization Multi-Agent Path Finding
Amazon Robotics, Boston, MA, USA · Boston College, Chestnut Hill, MA, USA · UAK holds concurrent appointments as an Amazon Scholar with Amazon Robotics and as a Professor of Computer Science at Boston College
RADAR: Redundancy-Aware Diffusion for Multi-Agent Communication Structure Generation
May 11, 2026Zhen Zhang, Wanjing Zhou, Juncheng Li +3Multi-Agent LLM Systems Multi-Agent System Optimization
National Key Laboratory for Novel Software Technology, Nanjing University, China · Zhejiang University · University of Oxford +1
TacoMAS: Test-Time Co-Evolution of Topology and Capability in LLM-based Multi-Agent Systems
May 10, 2026Chen Xu, Yicheng Hu, Ruizi Wang +4Multi-Agent LLM Systems Multi-Agent System Optimization
1Carnegie Mellon University · University of Science and Technology of China · 3National University of Singapore +1
SkillMAS: Skill Co-Evolution with LLM-based Multi-Agent System
May 10, 2026Shuai Pan, Yixiang Liu, Jiaye Gao +7Multi-Agent System Optimization LLM Agent Skill Learning
Shanghai Jiao Tong University · Central South University · OPPO
Rethinking Ratio-Based Trust Regions for Policy Optimization in Multi-Agent Reinforcement Learning
May 9, 2026Chulabhaya Wijesundara, Andrea Baisero, Zhongheng Li +3Multi-Agent System Optimization Policy Optimization
Northeastern University · STR · University of California, Irvine
AgentSlimming: Towards Efficient and Cost-Aware Multi-Agent Systems
May 9, 2026Yulang Chen, Haoxuan Peng, Jinyan Liu +3Multi-Agent LLM Systems Multi-Agent System Optimization
1Shanghai Jiao Tong University · 2Nanjing University · 3The University of Sydney +2
EvoMAS: Learning Execution-Time Workflows for Multi-Agent Systems
May 9, 2026Chengdong Xu, Kaiqiang Ke, Ziheng Liu +4Multi-Agent LLM Systems Multi-Agent System Optimization
Sun Yat-Sen University · ShanghaiTech University · Zhejiang University +1
ADKO: Agentic Decentralized Knowledge Optimization
May 8, 2026Lucas Nerone Rillo, Zhanhong Jiang, Nastaran Saadati +4Multi-Agent System Optimization AI Agents for Scientific Discovery
Iowa State University · New York University
Many-to-Many Multi-Agent Pickup and Delivery
May 8, 2026Ethan Schneider, Jingkai Chen, Tianyi Gu +3Multi-Agent System Optimization Multi-Robot Task Allocation
Institute of Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA 30332, USA · Symbotic Inc., Wilmington, MA 01887, USA · Northeastern University, Boston, MA 02115, USA
HMACE: Heterogeneous Multi-Agent Collaborative Evolution for Combinatorial Optimization
May 8, 2026Yuping Yan, Jirui Han, Fei Ming +2Multi-Agent LLM Systems Multi-Agent System Optimization
School of Engineering Westlake University
Multi-Objective Multi-Agent Bandits: From Learning Efficiency to Fairness Optimization
May 7, 2026John Wang, Mengfan XuMulti-Armed Bandits Multi-Agent System Optimization
University of Massachusetts Amherst
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
May 7, 2026Zhexuan Wang, Xuebo Liu, Li Wang +4Multi-Agent LLM Systems Multi-Agent System Optimization
Institute of Computing and Intelligence, Harbin Institute of Technology, Shenzhen, China.
Multiagent Stochastic Shortest Path Problem
May 7, 2026Martin Jonáš, Antonín Kučera, Vojtěch Kůr +2Multi-Agent System Optimization Multi-Agent Coordination
Faculty of Informatics, Masaryk University, Czechia
Active Learning for Communication Structure Optimization in LLM-Based Multi-Agent Systems
May 7, 2026Huchen Yang, Xinghao Dong, Dan Negrut +1Multi-Agent LLM Systems Multi-Agent System Optimization
University of Wisconsin–Madison
Uno-Orchestra: Parsimonious Agent Routing via Selective Delegation
May 6, 2026Zhiqing Cui, Haotong Xie, Jiahao Yuan +11Multi-Agent System Optimization Multi-Agent Orchestration
Project lead.
ARMATA: Auto-Regressive Multi-Agent Task Assignment
May 5, 2026Yazan Youssef, Aboelmagd Noureldin, Sidney GivigiMulti-Agent System Optimization Multi-Robot Task Allocation
Department of Electrical and Computer Engineering, Queen’s University, Kingston, ON, Canada · Department of Electrical and Computer Engineering at the Royal Military College of Canada, and the Department of Electrical and Computer Engineering at Queen’s University, both in Kingston, Canada · School of Computing, Queen’s University, Kingston, ON, Canada
Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation
May 4, 2026Jingchu Gai, Laixi ShiMulti-Agent System Optimization Markov Models
Machine Learning Department, Carnegie Mellon University. · Department of Electrical and Computer Engineering, Johns Hopkins University, MD 21286, USA.
Optimized and kinematically feasible multi-agent motion planning
May 3, 2026Anja Hellander, Kristoffer Bergman, Daniel AxehillConstrained Motion Planning Trajectory Optimization
Division of Automatic Control, Linköping University, Sweden · Saab AB, Linköping, Sweden
TeamTR: Trust-Region Fine-Tuning for Multi-Agent LLM Coordination
May 1, 2026Yi Xie, Siao Liu, Falong Fan +3Multi-Agent System Optimization Multi-Agent Coordination
Department of Electrical & Computer Engineering, University of Arizona · Future Science and Engineering College, Soochow University · INSAIT, Sofia University ”St. Kliment Ohridski” +1
NonZero: Interaction-Guided Exploration for Multi-Agent Monte Carlo Tree Search
May 1, 2026Sizhe Tang, Zuyuan Zhang, Mahdi Imani +1Multi-Agent System Optimization Multi-Agent Coordination
The George Washington University · Northeastern University
Learning to Act and Cooperate for Distributed Black-Box Consensus Optimization
May 1, 2026Zi-Bo Qin, Feng-Feng Wei, Tai-You Chen +1Multi-Agent System Optimization Multi-Agent Coordination
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China.
Agent Capsules: Quality-Gated Granularity Control for Multi-Agent LLM Pipelines
May 1, 2026Aninda RayLLM Inference Efficiency Multi-Agent LLM Systems
Split over $n$ resource sharing problem: Are fewer capable agents better than many simpler ones?
Apr 29, 2026Karthik Soma, Mohamed S. Talamali, Genki Miyauchi +3Multi-Agent System Optimization Multi-Agent Systems
MIST lab, École Polytechnique de Montréal, Montreal, Canada · School of Electrical and Electronic Engineering, The University of Sheffield, Sheffield, UK · Department of Computer and Information Science, University of Konstanz, Konstanz, Germany +1
Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems
Apr 23, 2026Ye Yu, Heming Liu, Haibo Jin +3Multi-Agent System Optimization LLM Agent Training
University of Illinois Urbana-Champaign, IL, USA
Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization
Apr 22, 2026Shan He, Runze Wang, Zhuoyun Du +4Multi-Agent System Optimization Learning to Optimize
Future Living Lab of Alibaba
A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing
Apr 22, 2026Samaresh Kumar Singh, Joyjit RoyMulti-Agent System Optimization Multi-Agent Coordination
Independent Researcher · Leander, Texas · Austin, Texas
AgenticRecTune: Multi-Agent with Self-Evolving Skillhub for Recommendation System Optimization
Apr 21, 2026Xidong Wu, Yue Zhuan, Ruoqiao Wei +7Multi-Agent LLM Systems Multi-Agent System Optimization
Google Mountain View, California, USA
Phase-Scheduled Multi-Agent Systems for Token-Efficient Coordination
Apr 19, 2026Mohit DubeyMulti-Agent LLM Systems Multi-Agent System Optimization
Open Gigantic
Hive: A Multi-Agent Infrastructure for Algorithm- and Task-Level Scaling
Apr 19, 2026Zizhang Luo, Yuhao Luo, Youwei Xiao +3LLM Inference Efficiency Multi-Agent LLM Systems
Peking University Beijing, China
Safe and Policy-Compliant Multi-Agent Orchestration for Enterprise AI
Apr 19, 2026Vinil Pasupuleti, Shyalendar Reddy Allala, Siva Rama Krishna Varma Bayyavarapu +1Multi-Agent System Optimization Multi-Agent Coordination
International Business Machines · International Business Machines (IBM) · South Carolina, United States +6

May 11, 2026, cs.LGJ/K move · Enter open · S save

Optimal and Scalable MAPF via Multi-Marginal Optimal Transport and Schrödinger Bridges

Usman A. Khan, Joseph W. Durham

Amazon Robotics, Boston, MA, USA · Boston College, Chestnut Hill, MA, USA · UAK holds concurrent appointments as an Amazon Scholar with Amazon Robotics and as a Professor of Computer Science at Boston College

Multi-Agent System Optimization Multi-Agent Path Finding Optimal Transport

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We consider anonymous multi-agent path finding (MAPF) where a set of robots is tasked to travel to a set of targets on a finite, connected graph. We show that MAPF can be cast as a special class of multi-marginal optimal transport (MMOT) problems with an underlying Markovian structure, under which the exponentially large MMOT collapses to a linear program (LP) polynomial in size. Focusing on the anonymous setting, we establish conditions under which the corresponding LP is feasible, totally unimodular, and consequently, yields min-cost, integral

(\{0,1\})

transports that do not overlap in both space and time. To adapt the approach to large-scale problems, we cast the MAPF-MMOT in a probabilistic framework via Schrödinger bridges. Under standard assumptions, we show that the Schrödinger bridge formulation reduces to an entropic regularization of the corresponding MMOT that admits an iterative Sinkhorn-type solution. The Schrödinger bridge, being a probabilistic framework, provides a shadow (fractional) transport that we use as a template to solve a reduced LP and demonstrate that it results in near-optimal, integral transports at a significant reduction in complexity. Extensive experiments highlight the optimality and scalability of the proposed approaches.

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