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Marchant, Nicolás; Quillien, Tadeg; Chaigneau, Sergio E. – Cognitive Science, 2023
The causal view of categories assumes that categories are represented by features and their causal relations. To study the effect of causal knowledge on categorization, researchers have used Bayesian causal models. Within that framework, categorization may be viewed as dependent on a likelihood computation (i.e., the likelihood of an exemplar with…
Descriptors: Classification, Bayesian Statistics, Causal Models, Evaluation Methods
Foster-Hanson, Emily; Leslie, Sarah-Jane; Rhodes, Marjorie – Cognitive Science, 2022
Generic language (e.g., "tigers have stripes") leads children to assume that the referenced category (e.g., tigers) is inductively informative and provides a causal explanation for the behavior of individual members. In two preregistered studies with 4- to 7-year-old children (N = 497), we considered the mechanisms underlying these…
Descriptors: Young Children, Error Correction, Beliefs, Classification
Rehder, Bob – Cognitive Science, 2017
This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…
Descriptors: Abstract Reasoning, Logical Thinking, Causal Models, Graphs