Multiagent System

Multiagent systems (MAS) research focuses on designing and analyzing systems composed of multiple interacting autonomous agents, aiming to achieve collective goals efficiently and robustly. Current research emphasizes addressing challenges like agent specialization, mitigating selfish behavior through subsidy design or norm enforcement, and developing scalable and verifiable control strategies using techniques such as control barrier functions and graph neural networks. This field is crucial for advancing various applications, including robotics, smart grids, and AI safety, by providing frameworks for coordinating complex interactions and ensuring desirable system-level outcomes.