1. INTRODUCTION. In this investigation we attempt to quantify expert reasoning to process boolean values 0 (FALSE) and 1 (TRUE) instead of large lists of atoms that form conditions. The human brain reasons by processing demodulated signals through axons and across synapses, which either fire or don't fire in a boolean fashion. Our approach bridges the current expert systems approach (see, e.g., Hayes-Roth et al.) and the old approaches, e.g., neural nets (McCulloch and Pitts) and associations (Nakano). It simplifies knowledge representation by reducing much of symbolic processing to efficient ANDing and ORing. An ultimate application of our approach would be an expert systems on a chip. A side effect of this would be the demise of inefficient, memory cluttering, list processing languages.