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Cognitive Domain Ontologies in lookup tables stored in a memristor string matching architecture

机译:存储在忆阻器字符串匹配体系结构中的查找表中的认知域本体

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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 platform. This paper examines how some of the components of a cognitive agent can be mapped onto lookup tables stored in memristor crossbar circuits capable of highly parallel string matching. 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). We show that CDOs can be implemented in lookup tables, and present a memristor crossbar circuit capable of storing these lookup tables very efficiently.
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,强烈需要在低功率平台上运行的实时代理。本文研究了如何将认知智能体的某些组件映射到存储在具有高度并行字符串匹配能力的忆阻器交叉开关电路中的查找表上。检查的代理是认知增强复杂事件处理(CECEP)架构。这是一种自主决策支持工具,可以像人一样进行推理,并可以增强基于代理的决策。它具有广泛的应用领域,包括自治系统,运筹学,情报分析和数据挖掘。 CECEP的最耗时且关键的组成部分之一是从描述为认知域本体(CDO)的存储库中挖掘知识。我们展示了CDO可以在查找表中实现,并展示了一种忆阻器纵横电路,该电路能够非常有效地存储这些查找表。

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