Formal Approaches in Categorization
The process of constructing concepts underpins our capacity to encode information in an efficient and competent manner and also, ultimately, our ability to think in terms of abstract ideas such as justice, love and happiness. But what are the mechanisms which correspond to psychological categorization processes? This book unites many prominent approaches in modelling categorization. Each chapter focuses on a particular formal approach to categorization, presented by the proponent(s) or advocate(s) of that approach, and the authors consider the relation of this approach to other models and the ultimate objectives in their research programmes. The volume evaluates progress that has been made in the field and where it goes from here. This is an essential companion to any scientist interested in the formal description of categorization and, more generally, in formal approaches to cognition. It will be the definitive guide to formal approaches in categorization research for years to come.
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10 Adaptive clustering models of categorization
11 cobweb models of categorization and probabilistic concept formation
12 The knowledge and resonance KRES model of category learning
13 The contribution and drawbacks of models to the study of concepts
14 Formal models of categorization insights from cognitive neuroscience
15 Comments on models and categorization theories the razors edge
9 The simplicity model of unsupervised categorization
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activation ALCOVE algorithm approach Ashby associated assumed assumption behaviour category learning category representations category structure Chapter classification cluster Cobweb Cobweb models codelength Cognitive Science Society computational concepts connectionist constraints Context theory COVIS cues Dirichlet process distribution dopamine effects egory encoding Equation example exemplar model experiment Experimental Psychology feedback Figure Gibbs sampling Griffiths Gureckis hierarchy human implementation input internal representations J. D. Smith Journal of Experimental KRES Kruschke layer mapping McLaren Medin memory models of categorization Murphy Neuroscience nodes Nosofsky objects observed outcome output parameter particle filter partition pattern perceptual performance Pothos predictions prior knowledge probabilistic probability prototype model prototype theory Psychological Review RASHNL Rehder relation relevant represented response Rosch rule rule-based Rumelhart selective attention semantic similarity simplicity model simulations specific stimuli stimulus dimensions SUSTAIN task theory tion units unsupervised categorization unsupervised learning values