Multi-Agent RL

ICLR 2024arXiv:2308.10848

#2

AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Weize Chen, Yusheng Su, Jingwei Zuo et al.

503

ICLR 2025arXiv:2406.04692

#3

Mixture-of-Agents Enhances Large Language Model Capabilities

Junlin Wang, Jue Wang, Ben Athiwaratkun et al.

294

ICLR 2024arXiv:2307.02485

#4

Building Cooperative Embodied Agents Modularly with Large Language Models

Hongxin Zhang, Weihua Du, Jiaming Shan et al.

273

ICML 2024arXiv:2310.03302

#5

MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation

Qian Huang, Jian Vora, Percy Liang et al.

language agentsmachine learning experimentationreact frameworkbenchmark evaluation+4

168

ICLR 2025arXiv:2406.07155

#6

Scaling Large Language Model-based Multi-Agent Collaboration

Chen Qian, Zihao Xie, YiFei Wang et al.

146

ICML 2024arXiv:2310.18940

#7

Language Agents with Reinforcement Learning for Strategic Play in the Werewolf Game

Zelai Xu, Chao Yu, Fei Fang et al.

reinforcement learninglarge language modelsstrategic decision-makingsocial deduction games+4

136

ICML 2024arXiv:2402.19446

#8

ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL

Yifei Zhou, Andrea Zanette, Jiayi Pan et al.

language model agentssequential decision-makingmulti-turn reinforcement learningtoken-level policy gradient+4

135

ICML 2024arXiv:2402.10207

#9

Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment

Rui Yang, Xiaoman Pan, Feng Luo et al.

multi-objective alignmenthuman preference alignmentreinforcement learning fine-tuningsupervised fine-tuning+4

125

ICLR 2025arXiv:2411.02337

#10

WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning

Zehan Qi, Xiao Liu, Iat Long Iong et al.

llm web agentsonline curriculum reinforcement learningself-evolving curriculumoutcome-supervised reward model+3

121

AAAI 2024arXiv:2308.11339

#11

ProAgent: Building Proactive Cooperative Agents with Large Language Models

Ceyao Zhang, Kaijie Yang, Siyi Hu et al.

120

NEURIPS 2025arXiv:2505.24298

#12

AREAL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning

Wei Fu, Jiaxuan Gao, Xujie Shen et al.

reinforcement learninglarge language modelsreasoning tasksasynchronous training+4

117

ICLR 2024arXiv:2308.02151

#13

Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

Weiran Yao, Shelby Heinecke, Juan Carlos Niebles et al.

108

NEURIPS 2025arXiv:2412.14161

#14

TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks

Frank (Fangzheng) Xu, Yufan Song, Boxuan Li et al.

105

NEURIPS 2025arXiv:2505.10978

#15

Group-in-Group Policy Optimization for LLM Agent Training

Lang Feng, Zhenghai Xue, Tingcong Liu et al.

105

ICML 2025arXiv:2409.08264

#16

Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale

Rogerio Bonatti, Dan Zhao, Francesco Bonacci et al.

102

ICML 2024arXiv:2402.08925

#17

MaxMin-RLHF: Alignment with Diverse Human Preferences

Souradip Chakraborty, Jiahao Qiu, Hui Yuan et al.

reinforcement learning from human feedbackreward model diversityhuman preference alignmentmixture of reward models+3

88

NEURIPS 2025arXiv:2505.23885

#18

OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

Mengkang Hu, Yuhang Zhou, Wendong Fan et al.

87

ICML 2025arXiv:2502.04180

#19

Multi-agent Architecture Search via Agentic Supernet

Guibin Zhang, Luyang Niu, Junfeng Fang et al.

83

ICLR 2024arXiv:2310.08887

#20

METRA: Scalable Unsupervised RL with Metric-Aware Abstraction

Seohong Park, Oleh Rybkin, Sergey Levine

75

ICML 2024arXiv:2308.01399

#21

Learning to Model the World With Language

Jessy Lin, Yuqing Du, Olivia Watkins et al.

world modelslanguage groundingmultimodal predictionself-supervised learning+4

71

ICLR 2025arXiv:2410.13825

#22

AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents

Ke Yang, Yao Liu, Sapana Chaudhary et al.

web agent groundingobservation space alignmentaction space alignmentllm-based agents+4

69

ICLR 2025arXiv:2407.07061

#23

Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence

Weize Chen, Ziming You, Ran Li et al.

68

ICML 2025arXiv:2311.18232

#24

LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models

Marwa Abdulhai, Isadora White, Charlie Snell et al.

67

ICLR 2025arXiv:2410.13232

#25

Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation

Hyungjoo Chae, Namyoung Kim, Kai Ong et al.

web navigation agentsworld modelslarge language modelsautonomous agents+4

65

ICLR 2025arXiv:2410.02506

#26

Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems

Guibin Zhang, Yanwei Yue, Zhixun Li et al.

multi-agent systemscommunication redundancytoken overhead reductionadversarial attack defense+3

64

ICLR 2025arXiv:2501.05707

#27

Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Vighnesh Subramaniam, Yilun Du, Joshua B Tenenbaum et al.

63

ICML 2025arXiv:2410.02958

#28

AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

Patara Trirat, Wonyong Jeong, Sung Ju Hwang

60

ICLR 2025arXiv:2410.14803

#29

DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent

Taiyi Wang, Zhihao Wu, Jianheng Liu et al.

54

ICLR 2024arXiv:2405.08550

#30

Learning Multi-Agent Communication from Graph Modeling Perspective

Shengchao Hu, Li Shen, Ya Zhang et al.

53

NEURIPS 2025arXiv:2505.23399

#31

GAM-Agent: Game-Theoretic and Uncertainty-Aware Collaboration for Complex Visual Reasoning

jusheng zhang, Yijia Fan, Wenjun Lin et al.

50

ICLR 2024arXiv:2306.09884

#32

Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX

Clément Bonnet, Daniel Luo, Donal Byrne et al.

48

ICML 2025arXiv:2505.00212

#33

Which Agent Causes Task Failures and When? On Automated Failure Attribution of LLM Multi-Agent Systems

Shaokun Zhang, Ming Yin, Jieyu Zhang et al.

46

AAAI 2024arXiv:2310.01207

#34

Learn to Follow: Decentralized Lifelong Multi-Agent Pathfinding via Planning and Learning

Alexey Skrynnik, Anton Andreychuk, Maria Nesterova et al.

45

ICML 2025arXiv:2408.00989

#35

On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents

Jen-Tse Huang, Jiaxu Zhou, Tailin Jin et al.

45

ICLR 2025arXiv:2410.18252

#36

Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models

Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux et al.

reinforcement learning from human feedbackoff-policy reinforcement learninglanguage model alignmentasynchronous training+4

43

ICML 2024arXiv:2403.00514

#37

Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning

Michal Nauman, Michał Bortkiewicz, Piotr Milos et al.

off-policy reinforcement learningactor-critic methodsregularization techniquesoverestimation bias+3

41

ICLR 2024arXiv:2302.08560

#38

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning

Harshit Sikchi, Qinqing Zheng, Amy Zhang et al.

41

ICLR 2024arXiv:2311.11385

#39

Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts

Ahmed Hendawy, Jan Peters, Carlo D'Eramo

41

NEURIPS 2025arXiv:2503.09501

#40

ReMA: Learning to Meta-Think for LLMs with Multi-agent Reinforcement Learning

Ziyu Wan, Yunxiang Li, Xiaoyu Wen et al.

meta-thinkingmulti-agent reinforcement learninglarge language modelsreasoning processes+4

40

reinforcement learning scalingtool-integrated reasoningspontaneous code executionmathematical problem solving+4

#41

Agentic RL Scaling Law: Spontaneous Code Execution for Mathematical Problem Solving

Xinji Mai, Haotian Xu, Xing W et al.

NEURIPS 2025

40

ICLR 2024arXiv:2403.04253

#42

Mastering Memory Tasks with World Models

Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran et al.

40

COLM 2025arXiv:2412.01928

#43

MALT: Improving Reasoning with Multi-Agent LLM Training

Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das et al.

reasoningmulti-agent systemspost-trainingreinforcement learning+1

37

NEURIPS 2025arXiv:2505.19591

#44

Multi-Agent Collaboration via Evolving Orchestration

Yufan Dang, Chen Qian, Xueheng Luo et al.

multi-agent collaborationlarge language modelsreinforcement learningdynamic orchestration+2

35

ICLR 2024arXiv:2401.15273

#45

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning

Chenyu Zhang, Han Wang, Aritra Mitra et al.

31

ICLR 2024arXiv:2401.10568

#46

CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents

Siyuan Qi, Shuo Chen, Yexin Li et al.

31

NEURIPS 2025arXiv:2506.01300

#47

ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding

Yiyang Zhou, Yangfan He, Yaofeng Su et al.

video understandingreward-driven agentsmulti-agent frameworkvision-language models+4

29

NEURIPS 2025arXiv:2501.15228

#48

Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning

Yiqun Chen, Lingyong Yan, Weiwei Sun et al.

retrieval-augmented generationmulti-agent reinforcement learningquery rewritingdocument retrieval+3

29

NEURIPS 2025arXiv:2504.00587

#49

AgentNet: Decentralized Evolutionary Coordination for LLM-based Multi-Agent Systems

Yingxuan Yang, Huacan Chai, Shuai Shao et al.

28

ICLR 2024arXiv:2404.01220

#50

Entity-Centric Reinforcement Learning for Object Manipulation from Pixels

Dan Haramati, Tal Daniel, Aviv Tamar

27

ECCV 2024arXiv:2409.18343

#51

Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving

Zhenghao Peng, Wenjie Luo, Yiren Lu et al.

autonomous drivingagent behavior modelingreinforcement learning fine-tuningdistribution shift+4

25

ICLR 2025arXiv:2501.16142

#52

Towards General-Purpose Model-Free Reinforcement Learning

Scott Fujimoto, Pierluca D'Oro, Amy Zhang et al.

model-free reinforcement learningmodel-based representationsvalue function linearizationgeneral-purpose rl+2

24

ICLR 2025arXiv:2407.07086

#53

Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models

Logan Cross, Violet Xiang, Agam Bhatia et al.

multi-agent reinforcement learningtheory of mindlarge language modelshierarchical planning+4

24

ICLR 2024arXiv:2312.04819

#54

Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning

Zican Hu, Zongzhang Zhang, Huaxiong Li et al.

24

ICLR 2024arXiv:2310.11971

#55

Improving Generalization of Alignment with Human Preferences through Group Invariant Learning

Rui Zheng, Wei Shen, Yuan Hua et al.

23

ICLR 2024arXiv:2305.12872

#56

Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game

Simin Li, Jun Guo, Jingqiao Xiu et al.

23

ICLR 2024arXiv:2306.10715

#57

Maximum Entropy Heterogeneous-Agent Reinforcement Learning

Jiarong Liu, Yifan Zhong, Siyi Hu et al.

23

ICCV 2025arXiv:2503.10200

#58

LVAgent: Long Video Understanding by Multi-Round Dynamical Collaboration of MLLM Agents

Boyu Chen, Zhengrong Yue, Siran Chen et al.

long video understandingmultimodal large language modelsagent collaborationtemporal context modeling+3

NEURIPS 2025arXiv:2502.04780

#59

SiriuS: Self-improving Multi-agent Systems via Bootstrapped Reasoning

Wanjia Zhao, Mert Yuksekgonul, Shirley Wu et al.

multi-agent systemslarge language modelsreasoning trajectoriesself-improving systems+3

NEURIPS 2025arXiv:2508.02085

#60

SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents

Yifu Guo, Jiaye Lin, Huacan Wang et al.

trajectory optimizationmulti-step reasoningllm-based agentsmonte carlo tree search+4

CVPR 2025arXiv:2502.19902

#61

Optimus-2: Multimodal Minecraft Agent with Goal-Observation-Action Conditioned Policy

Zaijing Li, Yuquan Xie, Rui Shao et al.

multimodal large language modelgoal-observation-action conditioningaction-guided behavior encoderopen-world task agents+4

ICLR 2024arXiv:2307.13372

#62

Submodular Reinforcement Learning

Manish Prajapat, Mojmir Mutny, Melanie Zeilinger et al.

ICLR 2025arXiv:2410.23208

#63

Kinetix: Investigating the Training of General Agents through Open-Ended Physics-Based Control Tasks

Michael Matthews, Michael Beukman, Chris Lu et al.

reinforcement learningphysics-based controlprocedural generationhardware-accelerated simulation+4

21

AAAI 2025arXiv:2407.09893

#64

Synergistic Multi-Agent Framework with Trajectory Learning for Knowledge-Intensive Tasks

Shengbin Yue, Siyuan Wang, Wei Chen et al.

21

NEURIPS 2025arXiv:2505.16394

#65

Raw2Drive: Reinforcement Learning with Aligned World Models for End-to-End Autonomous Driving (in CARLA v2)

Zhenjie Yang, Xiaosong Jia, Qifeng Li et al.

reinforcement learningautonomous drivingworld modelsmodel-based reinforcement learning+4

21

ICML 2025arXiv:2506.08379

#66

Reinforce LLM Reasoning through Multi-Agent Reflection

Yurun Yuan, Tengyang Xie

19

ICLR 2025arXiv:2502.05227

#67

Robotouille: An Asynchronous Planning Benchmark for LLM Agents

Gonzalo Gonzalez-Pumariega, Leong Yean, Neha Sunkara et al.

asynchronous planningllm agentslong-horizon tasksbenchmark environment+4

19

ICLR 2024arXiv:2405.11778

#68

Efficient Multi-agent Reinforcement Learning by Planning

Qihan Liu, Jianing Ye, Xiaoteng Ma et al.

ICLR 2025arXiv:2410.04612

#69

Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF

Zhaolin Gao, Wenhao Zhan, Jonathan Chang et al.

reinforcement learning from human feedbackmulti-turn dialoguepolicy optimizationcovariate shift+4

ICLR 2025arXiv:2503.21720

#70

Collab: Controlled Decoding using Mixture of Agents for LLM Alignment

Souradip Chakraborty, Sujay Bhatt, Udari Sehwag et al.

ICML 2024arXiv:2310.00344

#71

HarmonyDream: Task Harmonization Inside World Models

Haoyu Ma, Jialong Wu, Ningya Feng et al.

model-based reinforcement learningworld model learningobservation modelingreward modeling+4

ICML 2024arXiv:2406.19320

#72

Efficient World Models with Context-Aware Tokenization

Vincent Micheli, Eloi Alonso, François Fleuret

world modelsreinforcement learningsequence modelingdiscrete autoencoder+4

ICML 2025arXiv:2410.14972

#73

MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning

Suning Huang, Zheyu Zhang, Tianhai Liang et al.

ICML 2024arXiv:2404.18909

#74

Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty

Laixi Shi, Eric Mazumdar, Yuejie Chi et al.

multi-agent reinforcement learningdistributionally robust markov gamesrobust equilibrium strategiesgame-theoretic equilibria+4

AAAI 2024arXiv:2312.00198

#75

Optimal Attack and Defense for Reinforcement Learning

Jeremy McMahan, Young Wu, Xiaojin Zhu et al.

ICLR 2024arXiv:2310.01737

#76

Blending Imitation and Reinforcement Learning for Robust Policy Improvement

Xuefeng Liu, Takuma Yoneda, Rick Stevens et al.

NEURIPS 2025arXiv:2506.09033

#77

Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning

Haozhen Zhang, Tao Feng, Jiaxuan You

llm routingreinforcement learningsequential decision processmodel aggregation+3

NEURIPS 2025arXiv:2507.02554

#78

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench

Edan Toledo, Karen Hambardzumyan, Martin Josifoski et al.

ai research agentsautomated machine learningsearch policiesmcts algorithms+4

ICLR 2025arXiv:2410.22662

#79

EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents

Junting Chen, Checheng Yu, Xunzhe Zhou et al.

COLM 2025arXiv:2411.01747

#80

DynaSaur: Large Language Agents Beyond Predefined Actions

Dang Nguyen, Viet Dac Lai, Seunghyun Yoon et al.

FoX: Formation-Aware Exploration in Multi-Agent Reinforcement Learning

Yonghyeon Jo, Sunwoo Lee, Junghyuk Yum et al.

AAAI 2024arXiv:2308.11272

multi-agent reinforcement learningpartial observabilityexploration space scalabilityformation-based equivalence+4

ICML 2024arXiv:2403.06966

#82

Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts

Onur Celik, Aleksandar Taranovic, Gerhard Neumann

curriculum reinforcement learningmixture of expertsdiverse skill learningcontextual motion primitives+4

ICLR 2025arXiv:2502.12130

#83

Scaling Autonomous Agents via Automatic Reward Modeling And Planning

Zhenfang Chen, Delin Chen, Rui Sun et al.

automatic reward modelingmulti-step decision-makingllm-based agentstask planning+3

NEURIPS 2025arXiv:2505.12371

#84

MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical Tasks

Yinghao Zhu, Ziyi He, Haoran Hu et al.

multi-agent collaborationmedical question answeringlay summary generationelectronic health record modeling+3

ICLR 2025arXiv:2408.04203

#85

MMRole: A Comprehensive Framework for Developing and Evaluating Multimodal Role-Playing Agents

Yanqi Dai, Huanran Hu, Lei Wang et al.

ICLR 2025arXiv:2410.04631

#86

DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL

Mathias Jackermeier, Alessandro Abate

NEURIPS 2025arXiv:2503.14858

#87

1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities

Kevin Wang, Ishaan Javali, Michał Bortkiewicz et al.

ICLR 2025arXiv:2410.09486

#88

ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning

Yarden As, Bhavya, Lenart Treven et al.

reinforcement learningsafe explorationmodel-based rlprobabilistic dynamics model+3

AAAI 2024arXiv:2312.09539

#89

Situation-Dependent Causal Influence-Based Cooperative Multi-Agent Reinforcement Learning

Xiao Du, Yutong Ye, Pengyu Zhang et al.

ICLR 2024arXiv:2403.09859

#90

MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning

Zohar Rimon, Tom Jurgenson, Orr Krupnik et al.

AAAI 2025arXiv:2501.06773

#91

Pareto Set Learning for Multi-Objective Reinforcement Learning

Erlong Liu, Yu-Chang Wu, Xiaobin Huang et al.

multi-objective reinforcement learningpareto front learningdecomposition-based methodshypernetwork generation+3

AAAI 2024arXiv:2312.11118

#92

Explaining Reinforcement Learning Agents through Counterfactual Action Outcomes

Yotam Amitai, Yael Friedler, Ofra Amir

NEURIPS 2025arXiv:2505.21298

#93

Large Language Models Miss the Multi-agent Mark

Emanuele La Malfa, Gabriele La Malfa, Samuele Marro et al.

13

ICLR 2025arXiv:2411.00053

#94

ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration

Andrew Estornell, Jean-Francois Ton, Yuanshun Yao et al.

multi-agent collaborationactor-critic frameworklarge language modelsiterative dialog+2

13

ICLR 2025arXiv:2412.12089

#95

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

Eliot Xing, Vernon Luk, Jean Oh

reinforcement learningdifferentiable simulationmultiphysics simulationsoft body dynamics+4

13

ICML 2024arXiv:2405.06263

#96

Learning Latent Dynamic Robust Representations for World Models

Ruixiang Sun, Hongyu Zang, Xin Li et al.

model-based reinforcement learningworld modelsspatio-temporal maskingbisimulation principle+4

NEURIPS 2025arXiv:2506.12811

#97

Flow-Based Policy for Online Reinforcement Learning

Lei Lv, Yunfei Li, Yu Luo et al.

flow-based policyonline reinforcement learningwasserstein-2 regularizationmultimodal action distributions+3

ICLR 2024arXiv:2307.12062

#98

Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations

Yongyuan Liang, Yanchao Sun, Ruijie Zheng et al.

NEURIPS 2025arXiv:2505.20686

#99

Accelerating RL for LLM Reasoning with Optimal Advantage Regression

Kianté Brantley, Mingyu Chen, Zhaolin Gao et al.

reinforcement learninglarge language modelsreasoning taskspolicy optimization+4

ICLR 2024arXiv:2403.01112

#100

Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning

Hyungho Na, Yunkyeong Seo, Il-chul Moon

11