Efficient multi-agent communication via self-supervised information aggregation

C Guan, F Chen, L Yuan, C Wang… - Advances in …, 2022 - proceedings.neurips.cc
Utilizing messages from teammates can improve coordination in cooperative Multi-agent
Reinforcement Learning (MARL). To obtain meaningful information for decision-making …

Ace: Cooperative multi-agent q-learning with bidirectional action-dependency

C Li, J Liu, Y Zhang, Y Wei, Y Niu, Y Yang… - Proceedings of the …, 2023 - ojs.aaai.org
Multi-agent reinforcement learning (MARL) suffers from the non-stationarity problem, which
is the ever-changing targets at every iteration when multiple agents update their policies at …

Order matters: Agent-by-agent policy optimization

X Wang, Z Tian, Z Wan, Y Wen, J Wang… - arXiv preprint arXiv …, 2023 - arxiv.org
While multi-agent trust region algorithms have achieved great success empirically in solving
coordination tasks, most of them, however, suffer from a non-stationarity problem since …

DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems

Z Zheng, S Yao, Z Wang, X Tong, M Yuan… - arXiv preprint arXiv …, 2024 - arxiv.org
The min-max vehicle routing problem (min-max VRP) traverses all given customers by
assigning several routes and aims to minimize the length of the longest route. Recently …

Robust cooperative multi-agent reinforcement learning via multi-view message certification

L Yuan, T Jiang, L Li, F Chen, Z Zhang, Y Yu - Science China Information …, 2024 - Springer
Many multi-agent scenarios require message sharing among agents to promote
coordination, hastening the robustness of multi-agent communication when policies are …

Robust Multi-agent Communication via Multi-view Message Certification

L Yuan, T Jiang, L Li, F Chen, Z Zhang, Y Yu - arXiv preprint arXiv …, 2023 - arxiv.org
Many multi-agent scenarios require message sharing among agents to promote
coordination, hastening the robustness of multi-agent communication when policies are …

Efficient Communication via Self-Supervised Information Aggregation for Online and Offline Multiagent Reinforcement Learning

C Guan, F Chen, L Yuan, Z Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Utilizing messages from teammates can improve coordination in cooperative multiagent
reinforcement learning (MARL). Previous works typically combine raw messages of …