Applying Boolean discrete methods in the production of a real-valued probabilistic programming model

In this paper we explore the application of some notable Boolean methods, namely the Disjunctive Normal Form representation of logic table expansions, and apply them to a real-valued logic model which utilizes quantities on the range [0,1], [-1,1], [a,b], (x,y), (x,y,z), and etc. so as to produce logic of arbitrary range, precision, and dimensionality, e.g. enabling contemplation in notions of arbitrary data, colors, and spatial constructs, with the production of a probabilistic programming of a game character's logic in mathematical form.