A Bayesian stochastic formulation of Lanchester combat theory

In recent years the advancements in defense planning have created many challenging problems (deterministic and stochastic) for the scientist in the operations research area. Some of these challenges deal with the mechanism of incorporating field commanders' subjective information and engineers' prior assessments (weapons reliability) in the decision process. Furthermore, data acquisition in the probabilistic models should be admissible and non-prohibitive. This article addresses these two objectives, and presents a stochastic formulation that incorporates experts' opinion and requires feasible (easy and fast) information from the battlefield to assist the field commanders to review their strategies as often as they desire.