Algorithms for Generating Attribute Values for the Classification of Tactical Situations

ABSTRACT: In this paper we describe a series of algorithms that generate real-valued attributes used to classify tactical situations using an unsupervised machine learning system. Attributes for the classification of tactical situations include anchored and unanchored flanks, choke points, restricted avenues of attack and retreat, and interior line of support. 1. Introduction. Our research in Computational Military Tactical Planning (as introduced by Kewley and Embrechts[1]) suggests that, an unsupervised machine learning system (like Gennari and Langley’s ClassIT [2]) can make reasoned inferences abou