Composable Geo-Referenced Multi-Resolution Multi-Agent CA-Based DEVS, KIB, and PDE Models

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Including geometry in non-spatial automata elevates their expressiveness. This provides the context required to understand many natural and built systems and facilitate their development. Indeed, the scope and types of questions asked by domain experts are continually rising due to the varied and intertwined structures and dynamics of hybrid systems. This is especially evident for heterogeneous models required to solve complex problems. They benefit from using different modeling formalisms and simulation frameworks. In this paper, an approach targeting the development of composable, heterogeneous, multi-resolution, spatiotemporal models formalized according to modular, cellular automata, and multi-agent models grounded in parallel DEVS, Modelica, and Geo-referenced Knowledge Interchange Broker methods is proposed. This approach is used to develop a co-simulation framework supported by the DEVS-Suite and OpenModelica simulators and the Functional Mock-up Interface. A multi-scale model for human breast cancer biology highlights the use of the developed approach and the co-simulation framework.

Original languageEnglish (US)
Title of host publicationProceedings of the 2022 Winter Simulation Conference, WSC 2022
EditorsB. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, C.G. Corlu, L.H. Lee, E.P. Chew, T. Roeder, P. Lendermann
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages12
ISBN (Electronic)9798350309713
StatePublished - 2022
Event2022 Winter Simulation Conference, WSC 2022 - Guilin, China
Duration: Dec 11 2022Dec 14 2022

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Conference2022 Winter Simulation Conference, WSC 2022

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications


Dive into the research topics of 'Composable Geo-Referenced Multi-Resolution Multi-Agent CA-Based DEVS, KIB, and PDE Models'. Together they form a unique fingerprint.

Cite this