Ordered models for concept representation. (20th July 2020)

• Record Type: Journal Article
• Authors: Freund, Michael
• Is Part Of: Journal of logic and computation. Volume 30:Number 6(2020)
• Page Start: 1143
• Page End: 1181
• Publication Date: 2020-07-20
• Subjects: Categorization -- prototype theory -- categorial membership -- typicality -- inference relations -- nonmonotonic logic -- category-based induction -- resemblance theory -- deep learning; Logic programming -- Periodicals; Logic, Symbolic and mathematical -- Periodicals; Computational complexity -- Periodicals; 005.115
• DOI: 10.1093/logcom/exaa034
• Languages: English
• ISSNs: 0955-792X

Abstract

Abstract: Basic notions linked with concept theory can be accounted for by partial order relations. These orders translate the fact that, for an agent, an object may be seen as a better or a more typical exemplar of a concept than anyother. They adequately model notions linked with categorial membership, typicality and resemblance, without any of the drawbacks that are classically encountered in conjunction theory. An interesting consequence of such a concept representation is the possibility of using the tools of non-monotonic logic to address some well-known problems of cognitive psychology. Thus, conceptual entailment and concept induction can be reexamined in the framework of preferential inference relations. This leads to a rigorous definition of the basic notions used in the study of category-based induction.