Abstract
Cognitive agents are typically utilized in autonomous systems for automated decision making. These systems interact at real time with their environment and are generally heavily power constrained. Thus there is a strong need for a real time agent running on a low power computing platform. 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. This is an autonomous decision support tool that reasons like humans and enables enhanced agent-based decision-making. It has applications in a large variety of domains including autonomous systems, operations research, intelligence analysis, and data mining. One of the most time consuming and key components of CECEP is the mining of knowledge from a repository described as a Cognitive Domain Ontology (CDO). This paper looks at how CDOs can be mapped into neural form for realtime applications, and then examines their implementation on the IBM TrueNorth processor. The results show that the TrueNorth implementation generated correct answers for all the CDOs examined.
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