Real World System
Real-world system research focuses on designing, implementing, and verifying intelligent systems that operate effectively in complex, dynamic environments. Current efforts concentrate on developing self-adaptive architectures, leveraging AI (including large language models and deep learning) for tasks like task planning, tool usage, and data transformation, and employing digital twins for accurate simulation and optimization. This work is significant for improving the reliability and safety of critical systems across diverse domains, from wildfire detection to supply chain management, and for advancing the theoretical understanding of complex system behavior.
Papers
November 27, 2024
August 1, 2024
June 21, 2024
June 19, 2024
November 19, 2023
August 14, 2023
July 8, 2023
February 9, 2023
December 6, 2022
November 10, 2022
July 19, 2022
January 14, 2022
November 10, 2021