The reasoning system known as NARS constitutes a model of categorization. NARS is designed to be an adaptive system that works under the constraint of insufficient knowledge and resources. It consists of a categorical language, an experience-grounded semantics, a set of syllogistic inference rules, a dynamic memory structure, and a control mechanism that manages asynchronized parallel inference. In the system, reasoning and categorization are two aspects of the same underlying process. As a model of categorization, NARS unifies several existing theories.
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Document Type: Research Article
Department of Computer and Information Sciences, Temple University, Philadelphia, USA
Center for Research on Concepts and Cognition, Indiana University, Bloomington, USA
Publication date: June 1, 2006
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