Explanatory Frameworks in Complex Change and Resilience System
Modelling

Addis, Mark and Eckert, Claudia (2024). Explanatory Frameworks in Complex Change and Resilience System
Modelling.
Logic Journal of IGPL (In press).

DOI: https://doi.org/10.1093/jigpal/jzae087

URL: https://academic.oup.com/jigpal

Abstract

Conventional modelling and simulation have made huge progress in optimising flows for particular conditions. However heterogenous flows across system boundaries continue to pose significant problems for efficient resource allocation especially with respect to long term strategic planning and immediate problems about allocation to address particular resource shortages. Hospital systems which have various patient, staff and equipment flows are an important type of heterogenous flows. The approach taken here to modelling such flows is an engineering change prediction one. This enables margin modelling by producing system models in dependency matrices with different linkage types.

Change prediction approaches from engineering design can analyse where these bottlenecks in integrated systems would be so that resources can be deployed flexibility to avoid them and address them when they occur. Current state of the art of margin research can be furthered by identifying margins on multiple levels of system composition. It can usefully be complemented by a category theory based approach which allows representation of variable and constant properties of models under changing conditions, and the identification of flows within models. There is a difference between an explanatory framework for a model and how algorithms within the model work. Category theory is useful for formalising such explanatory frameworks as it can both structure systems and permit analysis of their applications in a complementary way.

Plain Language Summary

The use and value of category theory for modelling complex systems.

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