A logic of categorization

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,...

Full description

Saved in:
Bibliographic Details
Published inJournal of experimental & theoretical artificial intelligence Vol. 18; no. 2; pp. 193 - 213
Main Authors Wang, Pei, Hofstadter, Douglas
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 01.06.2006
Subjects
Categorization
Compositionality
Experience
Learning
Reasoning
Online AccessGet full text

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0952-813X
1362-3079
DOI:10.1080/09528130600557549