3 papers
cs.MA2026
MUTE: Return-Preserving Communication Unlearning for Efficient Multi-Agent Coordination
Rui Zuo, Qinwei Huang, Mingyang Li +3
Inter-agent communication is critical for coordinating Multi-Agent Reinforcement Learning (MARL) agents under partial observability to perform effectively in cooperative games; how…
cs.LG2026
Experience Constrained Hierarchical Federated Reinforcement Learning for Large-scale UAV Teams in Hazardous Environments
Qinwei Huang, Rui Zuo, Simon Khan +1
Conventional federated learning assumes that greater learner participation improves training performance, by leveraging abundant, independently generated local data. However, in fe…
cs.MA2025
Predictive Auxiliary Learning for Belief-based Multi-Agent Systems
Qinwei Huang, Stefan Wang, Simon Khan +2
The performance of multi-agent reinforcement learning (MARL) in partially observable environments depends on effectively aggregating information from observations, communications,…