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…

Though individual categorization or decision processes have been studied separately in many previous investigations, few studies have investigated how they interact by using a two-stage task of first categorizing and then deciding. To address this issue, we investigated a categorization-decision task in two experiments. In both, participants were…

We explore different ways in which the human visual system can adapt for perceiving and categorizing the environment. There are various accounts of supervised (categorical) and unsupervised perceptual learning, and different perspectives on the functional relationship between perception and categorization. We suggest that common experimental…

Propositional attitude verbs, such as "think" and "want," have long held interest for both theoretical linguists and language acquisitionists because their syntactic, semantic, and pragmatic properties display complex interactions that have proven difficult to fully capture from either perspective. This paper explores the…

Six experiments investigated variables predicted to influence subjects' tendency to classify items by a single property ("rule-based" responding) instead of overall similarity, following the paradigm of Norenzayan et al. (2002, "Cognitive Science"), who found that European Americans tended to give more "logical"…

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we…

Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…

This study investigated the relative contribution of perception/cognition and language-specific semantics in nonverbal categorization of spatial relations. English and Korean speakers completed a video-based similarity judgment task involving containment, support, tight fit, and loose fit. Both perception/cognition and language served as resources…

We investigate the hypothesis that our conceptual systems provide two formally distinct ways of representing categories by investigating the manner in which lexical nominals (e.g., "tree," "picnic table") and phrasal nominals (e.g., "black bird," "birds that like rice") are interpreted. Four experiments found that lexical nominals may be mapped…