Fang-Ting Gu

Graph Neural Network-Driven Adaptive MARL with Meta-Learning for Resilient Dynamic Optimization of Sports Building Facilities

We propose a decentralized multi-agent reinforcement learning (MARL) framework enhanced with graph neural networks (GNNs) for dynamic scheduling optimization in sports buildings, addressing the limitations of conventional centralized approaches. The system models each facility as an autonomous agent that learns adaptiv...