Complex System

Complex systems research aims to understand the emergent behavior of interconnected entities, often exhibiting unpredictable dynamics despite relatively simple individual components. Current research focuses on developing and applying advanced modeling techniques, including graph neural networks, Hamiltonian neural networks, and large language models integrated with agent-based models, to analyze diverse systems ranging from social networks to physical processes. These efforts improve prediction accuracy, enhance interpretability of complex system behavior, and enable more efficient simulations, ultimately impacting fields like predictive maintenance, climate modeling, and policy-making.