Abstract
This paper discusses challenges for M&S if it is to be increasingly important to decision aiding and policy analysis. It suggests an approach that—from the outset of a policy analysis project—incorporates M&S of a varied resolution with the intent that (1) the results of analysis will be communicated with a relatively simple model and corresponding narrative that scans the system problem in breadth, having been informed by richer modeling, and (2) the broad view is supplemented by the selective detail (zooms) and selected change of the perspective as needed. This is not just a matter of “dumbing down” communication, but a matter of thinking about both forests and trees from the outset and about designing analytic tools accordingly. It will also enable exploratory analysis amidst uncertainty and disagreement, which is central to modern policy analysis and decision-aiding. All of this poses significant challenges for those who design and build M&S.
Author supplied keywords
- base and lumped models
- contextual abstraction
- decision making under deep uncertainty (DMDU)
- exploratory analysis
- families of models
- modeling and simulation
- modeling for policy analysis
- multimodeling
- multiperspective modeling (MRMPM)
- multiresolution
- multiresolution modeling (MRM)
- qualitative modeling
- robust decision making (RDM)
Cite
CITATION STYLE
Davis, P. K. (2023). Broad and Selectively Deep: An MRMPM Paradigm for Supporting Analysis. Information (Switzerland), 14(2). https://doi.org/10.3390/info14020134
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