FIGURE 6.1 Old-think on model families.

In one sense, families of models have been around for years, but mostly on viewgraphs. In old-think ( Figure 6.1 ), moreover, they were formed by legislating that existing models at different levels of resolution would be considered a family and that detailed models would be used to generate data calibrating less-detailed models.

The results of most efforts along this line have been disappointing, if not downright failures. First, the models declared to be family members often were only casually related. Connecting them proved difficult and ambiguous. In part as a result, but also because of flawed theory, the calibration efforts failed. High-resolution models, for example, often predicted attrition and movement rates that greatly exceeded observed reality—presumably because they were not yet sufficiently complete to reflect many of the delays and other frictional effects that occur in real military operations. 1 Also, the high-resolution models often did not address key features of the problem. That is, they had insufficient scope. In other cases, the high-resolution models were credible, but the low-resolution models had no “hooks” for reflecting the high-resolution results. For example, they depended only on deterministic averages of higher-resolution phenomena when statistical or distributional information was critical. The general problem is that models that have not been designed for cross-calibration are often difficult to relate to one another.


As an example of the difficulties here, suppose that one wants to use a high-resolution simulation of company-level battle to calibrate the attrition rates of a higher-level model. A company, once it is in battle, may have a very short but intense period of attrition. However, most of the time such a company is not in such a battle. Further, there may be many hours of preparation before any such battle occurs. Accounting for these matters in attempting to provide “average rates” remains extremely difficult conceptually and was beyond the simulation and computational states of the art in past decades.

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