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

机译:一种将认知领域本体映射到IBM TrueNorth Neurosynaptic System的模式匹配方法

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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.
机译:认知主体通常在自治系统中用于自动决策。这些系统与其环境实时交互,并且通常受功率限制。因此,强烈需要针对这些系统在低功率计算平台上运行的实时代理。本文研究了如何将认知代理的某些组件映射到IBM TrueNorth神经突触系统上,从而以低功耗实现实时性能。检查的代理是认知增强复杂事件处理(CECEP)架构。尽管CECEP专为自主决策而设计,但它也可用于运筹学,情报分析和数据挖掘。 CECEP的关键组成部分之一是认知领域本体(CDO),用于根据情境输入和约束从大型知识库中挖掘决策。由于CDO是CECEP中最耗时和耗电的部分,因此我们在TrueNorth处理器上通过将CDO的解决方案空间映射为模式匹配形式来实现它们。

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