Hidetsugu Uchida

Spatial Graph-Based Multi-Agent Reinforcement Learning for Asynchronous Coordination with Dynamic Entities

Real-world multi-agent systems operate in dynamic environments characterized by asynchrony arising from long-horizon planning, varying numbers of entities, and changes in spatial layouts. Although multi-agent reinforcement learning (MARL) has introduced methods for asynchronous decisionmaking and generalization to vari...