Automating the Acquisition of Tactical Knowledge for Military Missions

It is widely accepted that acquisition of the knowledge behind military tactics has been one limiting factor in the development of computer generated forces (CGF) for training simulations. This has been addressed by several researchers with varying degrees of success. A system capable of building a knowledge base directly from a dialogue with a subject-matter expert (SME) could significantly reduce the human effort involved in capturing the knowledge and representing it directly in the modeling language. Because of its highly modular and hierarchical nature, the context-based reasoning (CxBR) modeling paradigm lends itself very well to facilitating the knowledge acquisition process for tactical behaviors. This paper describes an investigation into using CxBR as the foundation for a system that creates a (partial) model of tactical behavior through an interactive process with an SME. Through a sequence of queries from the system, the SME is progressively asked to provide details about the contexts that compose the context-based model of the expert's tactical know-how. A prototype was built and evaluated. A comparison to the effort taken to manually develop a knowledge base is reported. We use the simulation of a non-trivial maritime military confrontation as the benchmark for the comparisons.