Data-driven behavioural modelling for military applications

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This article investigates the possibilities for creating behavioural models of military decision making in a data-driven manner. As not much data from actual operations is available, and data cannot easily be created in the military context, most approaches use simulators to learn behaviour. A simulator is however not always available or is difficult to create. This study focusses on the creation of behavioural models from data that was collected during a field exercise. As data in general is limited, noisy and erroneous, this makes the creation of realistic models challenging. Besides using the traditional approach of hand-crafting a model based on data, we investigate the emerging research area of imitation learning. One of its techniques, reward engineering, is applied to learn the behaviour of soldiers in an urban warfare operation. Basic, but realistic, soldier behaviour is learned, which lays the groundwork for more elaborate models in the future.

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data-driven_behavioural_modelling_for_military_applications_final-7.pdf	1.33 MB