TY - GEN
T1 - Composable Geo-Referenced Multi-Resolution Multi-Agent CA-Based DEVS, KIB, and PDE Models
AU - Sarjoughian, Hessam S.
AU - Zhang, Chao
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
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U2 - 10.1109/WSC57314.2022.10015526
DO - 10.1109/WSC57314.2022.10015526
M3 - Conference contribution
AN - SCOPUS:85147424063
T3 - Proceedings - Winter Simulation Conference
SP - 2166
EP - 2177
BT - Proceedings of the 2022 Winter Simulation Conference, WSC 2022
A2 - Feng, B.
A2 - Pedrielli, G.
A2 - Peng, Y.
A2 - Shashaani, S.
A2 - Song, E.
A2 - Corlu, C.G.
A2 - Lee, L.H.
A2 - Chew, E.P.
A2 - Roeder, T.
A2 - Lendermann, P.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Winter Simulation Conference, WSC 2022
Y2 - 11 December 2022 through 14 December 2022
ER -