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Models of Concepts *
Author(s) -
Cohen Benjamin,
Murphy Gregory L.
Publication year - 1984
Publication title -
cognitive science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.498
H-Index - 114
eISSN - 1551-6709
pISSN - 0364-0213
DOI - 10.1207/s15516709cog0801_2
Subject(s) - computer science , schema (genetic algorithms) , variety (cybernetics) , cognitive science , connectionism , representation (politics) , set (abstract data type) , artificial intelligence , knowledge representation and reasoning , epistemology , psychology , machine learning , artificial neural network , programming language , philosophy , politics , political science , law
Over the last 10 years research on concepts has produced on important new theory known as prototype theory. Despite its empirical successes, prototype theory has been challenged by various arguments purporting to show its descriptive inadequacy for a variety of phenomena, including complex concepts and quantification. These arguments are primarily based on a set theoretic model of concepts. We consider the advantages and disadvantages of the set‐theoretic approach and argue that if we instead model concepts as knowledge representations of a certain kind, it is possible not only to answer prototype theory's critics, but to address more fundamental issues in the theory of concepts. We also consider the implications of these different approaches for psychology, linguistics, and artificial intelligence (AI). To substantiate our claims, a knowledge representation model of prototype theory is outlined, based on work in schema theory and AI knowledge representation.