Wilsdorf, Pia and Henning, Philipp and Kreikemeyer, Justin N. and Kliefoth, Marcel and Baltrusch, Simone and Uhrmacher, Adelinde M. (2025) Self-Adaptive Simulation Models: A Case Study in Cell Biology. In: 28th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), 17-19 September 2025, Prag, Tschechische Republik. Proceedings, published by IEEE, pp. 1-8.
Full text not available from this repository.Abstract
Artificial intelligence is transforming science into a highly automated process, accelerating the pace of scientific discovery. We argue that automatically adapting simulation models to new data, knowledge about mechanisms, or research questions plays a key role in this change of paradigm. To this end, we explore the use of the MAPE- K (Monitor, Analyze, Plan, and Execute, over a shared Knowledge base) framework from self-adaptive software systems to realize a self-adaptive simulation model. Such a model will preserve its currency, reveal new insights, and provide enhanced predictions as well as effective feedback to the observed system. As a case study, we use a cell-biological model of glucose-stimulated insulin secretion. We conclude with a discussion relating our approach to digital twins and current developments in inferring simulation models from data that opens up questions to be pursued in future research.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | doi: 10.1109/DS-RT68115.2025.11185996 |
| Projects: | E-MoSi-CA |
