Dispersed combat as mass action with finite search

Abstract

Improvements to models of battle attrition are necessary because current models cannot explain battle attrition. Agent based simulations indicate that calculated attrition is substantially different when agents are not assumed to have unlimited detection capabilities. However, agent based models are limited to small force sizes and there is no evidence that the changes in calculated attrition occur for large force sizes. We develop a probabilistic model, based on Bernoulli trials, to check if limited detection capabilities result in significant changes to calculated attrition when force sizes are large, as in battle datasets. Our model is a search model and we convert it to an attrition model via the same processes used in current models, and include the same assumptions for factors other than detection range. We find two series solutions to the model, one for small force sizes, the other for large force sizes, and find numerically that the two solutions strongly overlap. The new model makes a difference to calculated attrition when force sizes are small, but not when they are large. However, the model makes a difference to calculated attrition for all force sizes if the battlefield area is increased to maintain a sparse force density. Our approach is mathematical, not requiring application knowledge, and several of the assumptions underlying mass action models are raised in our discussion. References

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