"multi-agent reinforcement learning" Papers
65 papers found • Page 1 of 2
Conference
Adaptive Context Length Optimization with Low-Frequency Truncation for Multi-Agent Reinforcement Learning
Wenchang Duan, Yaoliang Yu, Jiwan He et al.
Advantage Alignment Algorithms
Juan Duque, Milad Aghajohari, Timotheus Cooijmans et al.
A Generalist Hanabi Agent
Arjun V Sudhakar, Hadi Nekoei, Mathieu Reymond et al.
AgentMixer: Multi-Agent Correlated Policy Factorization
Zhiyuan Li, Wenshuai Zhao, Lijun Wu et al.
A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
Mingyang Liu, Gabriele Farina, Asuman Ozdaglar
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
Anjie Liu, Jianhong Wang, Samuel Kaski et al.
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
Laixi Shi, Jingchu Gai, Eric Mazumdar et al.
Bridging Training and Execution via Dynamic Directed Graph-Based Communication in Cooperative Multi-Agent Systems
Zhuohui Zhang, Bin He, Bin Cheng et al.
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara et al.
DoF: A Diffusion Factorization Framework for Offline Multi-Agent Reinforcement Learning
Chao Li, Ziwei Deng, Chenxing Lin et al.
Efficient Multi-agent Offline Coordination via Diffusion-based Trajectory Stitching
Lei Yuan, Yuqi Bian, Lihe Li et al.
Empirical Study on Robustness and Resilience in Cooperative Multi-Agent Reinforcement Learning
Simin Li, Zihao Mao, Hanxiao Li et al.
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Alexander DeRieux, Walid Saad
Exponential Topology-enabled Scalable Communication in Multi-agent Reinforcement Learning
Xinran Li, Xiaolu Wang, Chenjia Bai et al.
FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning
Woosung Koh, Wonbeen Oh, Siyeol Kim et al.
GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL
Lang Qin, Ziming Wang, Runhao Jiang et al.
High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning
Qinyu Xu, Yuanyang Zhu, Xuefei Wu et al.
Hypothetical Minds: Scaffolding Theory of Mind for Multi-Agent Tasks with Large Language Models
Logan Cross, Violet Xiang, Agam Bhatia et al.
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
Yiqun Chen, Lingyong Yan, Weiwei Sun et al.
InvestESG: A multi-agent reinforcement learning benchmark for studying climate investment as a social dilemma
Xiaoxuan Hou, Jiayi Yuan, Joel Z Leibo et al.
Investigating Relational State Abstraction in Collaborative MARL
Sharlin Utke, Jeremie Houssineau, Giovanni Montana
Learn How to Query from Unlabeled Data Streams in Federated Learning
Yuchang Sun, Xinran Li, Tao Lin et al.
LOPT: Learning Optimal Pigovian Tax in Sequential Social Dilemmas
Yun Hua, Shang Gao, Wenhao Li et al.
MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
Elena Zamaraeva, Christopher Collins, George Darling et al.
MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning
Sizhe Tang, Jiayu Chen, Tian Lan
Mean-Field Sampling for Cooperative Multi-Agent Reinforcement Learning
Emile Anand, Ishani Karmarkar, Guannan Qu
MOSDT: Self-Distillation-Based Decision Transformer for Multi-Agent Offline Safe Reinforcement Learning
Yuchen Xia, Yunjian Xu
Multi-Agent Reinforcement Learning with Communication-Constrained Priors
Guang Yang, Jingwen Qiao, Tianpei Yang et al.
OPHR: Mastering Volatility Trading with Multi-Agent Deep Reinforcement Learning
Zeting Chen, Xinyu Cai, Molei Qin et al.
Rainbow Delay Compensation: A Multi-Agent Reinforcement Learning Framework for Mitigating Observation Delays
Songchen Fu, Siang Chen, Shaojing Zhao et al.
ReMA: Learning to Meta-Think for LLMs with Multi-agent Reinforcement Learning
Ziyu Wan, Yunxiang Li, Xiaoyu Wen et al.
Revisiting Multi-Agent World Modeling from a Diffusion-Inspired Perspective
Yang Zhang, Xinran Li, Jianing Ye et al.
Sequential Multi-Agent Dynamic Algorithm Configuration
Chen Lu, Ke Xue, Lei Yuan et al.
SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning
Xu Wan, Chao Yang, Cheng Yang et al.
Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization
Tianxu Li, Kun Zhu
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
Hyungho Na, Kwanghyeon Lee, Sumin Lee et al.
Understanding Individual Agent Importance in Multi-Agent System via Counterfactual Reasoning
Jianming Chen, Yawen Wang, Junjie Wang et al.
Vision-Based Generic Potential Function for Policy Alignment in Multi-Agent Reinforcement Learning
Hao Ma, Shijie Wang, Zhiqiang Pu et al.
Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning
Sunwoo Lee, Jaebak Hwang, Yonghyeon Jo et al.
Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
Yiyuan Pan, Zhe Liu, Hesheng Wang
Cautiously-Optimistic Knowledge Sharing for Cooperative Multi-Agent Reinforcement Learning
Yanwen Ba, Xuan Liu, Xinning Chen et al.
ConcaveQ: Non-monotonic Value Function Factorization via Concave Representations in Deep Multi-Agent Reinforcement Learning
Huiqun Li, Hanhan Zhou, Yifei Zou et al.
Controlling Behavioral Diversity in Multi-Agent Reinforcement Learning
Matteo Bettini, Ryan Kortvelesy, Amanda Prorok
Detecting Influence Structures in Multi-Agent Reinforcement Learning
Fabian Raoul Pieroth, Katherine Fitch, Lenz Belzner
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
Yizhe Huang, Anji Liu, Fanqi Kong et al.
FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learning
Wenzhe Li, Zihan Ding, Seth Karten et al.
FoX: Formation-Aware Exploration in Multi-Agent Reinforcement Learning
Yonghyeon Jo, Sunwoo Lee, Junghyuk Yum et al.
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
Bor Jiun Lin, Chun-Yi Lee
Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-Agent Reinforcement Learning
Zeyang Liu, Lipeng Wan, Xinrui Yang et al.
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.