A pattern matching approach to map cognitive domain ontologies to the IBM TrueNorth Neurosynaptic System

Cognitive agents are typically utilized in autonomous systems for automated decision making. These systems interact in real time with their environments and are generally heavily power constrained. Thus there is a strong need for a real time agent running on a low power computing platform for these systems. This paper examines how some of the components of a cognitive agent can be mapped onto the IBM TrueNorth neurosynaptic system to achieve real time performance at low power. The agent examined is the Cognitively Enhanced Complex Event Processing (CECEP) architecture. Although it is geared towards autonomous decision making, CECEP also has applications in operations research, intelligence analysis, and data mining. One of the key components of CECEP is the Cognitive Domain Ontology (CDO), used for mining decisions from a large knowledge repository based on situational inputs and constraints. As CDOs are the most time and power consuming part of CECEP, we implemented them on the TrueNorth processor by mapping the solution space of CDOs into a pattern matching form.