Poster "multi-agent reinforcement learning" Papers
27 papers found
A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning
Anjie Liu, Jianhong Wang, Samuel Kaski et al.
eQMARL: Entangled Quantum Multi-Agent Reinforcement Learning for Distributed Cooperation over Quantum Channels
Alexander DeRieux, Walid Saad
High-order Interactions Modeling for Interpretable Multi-Agent Q-Learning
Qinyu Xu, Yuanyang Zhu, Xuefei Wu et al.
Improving Retrieval-Augmented Generation through Multi-Agent Reinforcement Learning
Yiqun Chen, Lingyong Yan, Weiwei Sun 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
MOSDT: Self-Distillation-Based Decision Transformer for Multi-Agent Offline Safe Reinforcement Learning
Yuchen Xia, Yunjian Xu
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.
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.
Wonder Wins Ways: Curiosity-Driven Exploration through Multi-Agent Contextual Calibration
Yiyuan Pan, Zhe Liu, Hesheng Wang
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.
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
Bor Jiun Lin, Chun-Yi Lee
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
Xinran Li, Zifan LIU, Shibo Chen et al.
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
Hyungho Na, IL CHUL MOON
Major-Minor Mean Field Multi-Agent Reinforcement Learning
Kai Cui, Christian Fabian, Anam Tahir et al.
Modelling Competitive Behaviors in Autonomous Driving Under Generative World Model
Guanren Qiao, Guiliang Liu, Guorui Quan et al.
Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy
Riqiang Gao, Florin-Cristian Ghesu, Simon Arberet et al.
Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing
Amutheezan Sivagnanam, Ava Pettet, Hunter Lee et al.
Near-Optimal Reinforcement Learning with Self-Play under Adaptivity Constraints
Dan Qiao, Yu-Xiang Wang
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty
Laixi Shi, Eric Mazumdar, Yuejie Chi et al.
Sequential Asynchronous Action Coordination in Multi-Agent Systems: A Stackelberg Decision Transformer Approach
Bin Zhang, Hangyu Mao, Lijuan Li et al.