(as part of the IEEE Computer Society Distinguished Visitors Program, www.computer.org/web/chapters/dvp)

ABSTRACT:

The conventional approach to model construction for simulation is to focus on a single model and follow a more or less structured development cycle. Why should we put in twice the time and effort to develop two models rather than one? The answer lies in the fact that like most greedy heuristics, short-sightedness at the beginning may be much more costly in the end. This talk champions the cause of the pairs-of-models approach. We show how this approach eventually leads to better results than initially attempting to construct a complex model, followed later by having to revert to a simpler model when increasing complexity makes progress hard to achieve. We show how pairs-of-models development can be supported by computational tools for relating structure and behavior between models. Benefits of pairs of models, and eventually families of models, include the ability to perform mutual cross-calibration, avoid the usual difficulties in harmonizing the underlying ontologies, and narrow the search for plausible parameter assignments.