Why do simple combat models favour the attacker?

Abstract

Battle is complex, and no study can take every possible factor into account. Therefore the paper starts from the premise that it is the analyst’s prerogative to define the bounds of the model that he selects to address a given problem. Within this problem space, there is a tradable balance between simulating a feature of the system explicitly in the model, and representing it using the input data. Complex models emphasize the former, simple models emphasize the latter. From our experience, it would seem that simple models favour the attacker. The paper aims to demonstrate, using worked examples in different areas of battle modelling (e.g. movement, surveillance and attrition) that the more complex the model, the harder it is for the attacker particularly to achieve his aim. The tentative conclusion is that there is nothing inherent in the mathematics of simple models that favours the attacker – it is the subconscious way in which we use them. By feeding simple models with ‘naïve’ data, we can easily fall into the trap of ignoring the effects of ‘combat degradation’, without being aware that we have done so. By becoming aware of the potential problems, we can improve our model selection and use.