Psychology abounds with vigorous debates about the need for one or more underlying mental processes or systems to explain empirical observations. The field of category learning provides an excellent exemplar. We present a critical examination of this field focusing on empirical, methodological, and mathematical modeling considerations. We review what is often presented as the "best evidence" for multiple systems of category learning and critique the evidence by considering three questions: (1) Are multiple-systems accounts the only viable explanations for reported effects? (2) Are the inferences sound logically and methodologically? (3) Are the mathematical models that can account for behavior sufficiently constrained, and are alternative (...
This article proposes that learning of categories based on cause-effect relations is guided by causa...
The ability to learn categories and classify new items or experiences is an essential function for e...
erties of a category based on data (i.e., category members and the features that describe them) but ...
A substantial and growing body of evidence from cognitive neuroscience supports the concept of multi...
Some researchers have argued that the category learning literature is conclusive: people learn to g...
textCategory learning is an essential cognitive function. Empirical evidence and theoretical reasons...
Models of Category Learning Pat Langley 1 (langley@isle.org) Institute for the Study of Learning...
We explore humans' rule-based category learning using analytic approaches that highlight their psych...
Multiple theories of category learning converge on the idea that there are two systems for categoriz...
<div><p>We explore humans’ rule-based category learning using analytic approaches that highlight the...
A class of dual-system theories of categorization assumes a categorization system based on actively ...
This paper examines the ability of a dual-system, formal model of categorization COVIS (Ashby, Paul...
textCategorization is a fundamental process that underlies much of cognition. People form categorie...
A central idea in many successful models of category learning—including the Generalized Context Mode...
A central idea in many successful models of category learning—including the Generalized Context Mode...
This article proposes that learning of categories based on cause-effect relations is guided by causa...
The ability to learn categories and classify new items or experiences is an essential function for e...
erties of a category based on data (i.e., category members and the features that describe them) but ...
A substantial and growing body of evidence from cognitive neuroscience supports the concept of multi...
Some researchers have argued that the category learning literature is conclusive: people learn to g...
textCategory learning is an essential cognitive function. Empirical evidence and theoretical reasons...
Models of Category Learning Pat Langley 1 (langley@isle.org) Institute for the Study of Learning...
We explore humans' rule-based category learning using analytic approaches that highlight their psych...
Multiple theories of category learning converge on the idea that there are two systems for categoriz...
<div><p>We explore humans’ rule-based category learning using analytic approaches that highlight the...
A class of dual-system theories of categorization assumes a categorization system based on actively ...
This paper examines the ability of a dual-system, formal model of categorization COVIS (Ashby, Paul...
textCategorization is a fundamental process that underlies much of cognition. People form categorie...
A central idea in many successful models of category learning—including the Generalized Context Mode...
A central idea in many successful models of category learning—including the Generalized Context Mode...
This article proposes that learning of categories based on cause-effect relations is guided by causa...
The ability to learn categories and classify new items or experiences is an essential function for e...
erties of a category based on data (i.e., category members and the features that describe them) but ...