Representing Knowledge and Experience in RPDAgent
John A. Sokolowski · 2007
Military simulations lack algorithms that adequately describe the cognitive decision process employed by military commanders. This is especially true at the operational level of warfare. Research was undertaken to improve upon these algorithms. What resulted was a model named RPDAgent that was able to mimic the human decision process and produce decisions that were equivalent to those made by humans for a given operational decision scenario. Key to the functioning of this model was its method for representing knowledge and experience. RPDAgent captured important concepts defined by Recognition-Primed Decision making. By modeling these concepts, it produced a unique and effective methodology for representing the experience needed to define complex decision-making.