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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
Fabian Tomaschek; Michael Ramscar; Jessie S. Nixon – Cognitive Science, 2024
Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences--and the relations between the elements they comprise--are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the…
Descriptors: Sequential Learning, Learning Processes, Serial Learning, Executive Function
Zheng, Rong; Busemeyer, Jerome R.; Nosofsky, Robert M. – Cognitive Science, 2023
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…
Descriptors: Classification, Decision Making, Task Analysis, Feedback (Response)
Onnis, Luca; Lim, Alfred; Cheung, Shirley; Huettig, Falk – Cognitive Science, 2022
Prediction is one characteristic of the human mind. But what does it mean to say the mind is a "prediction machine" and "inherently forward looking" as is frequently claimed? In natural languages, many contexts are not easily predictable in a forward fashion. In English, for example, many frequent verbs do not carry unique…
Descriptors: Prediction, Language Processing, Reading Processes, Task Analysis
Lau, Jey Han; Clark, Alexander; Lappin, Shalom – Cognitive Science, 2017
The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary…
Descriptors: Grammar, Probability, Sentences, Language Research
Jung, Wookyoung; Hummel, John E. – Cognitive Science, 2015
Theories of relational concept acquisition (e.g., schema induction) based on structured intersection discovery predict that relational concepts with a probabilistic (i.e., family resemblance) structure ought to be extremely difficult to learn. We report four experiments testing this prediction by investigating conditions hypothesized to facilitate…
Descriptors: Schemata (Cognition), Concept Formation, Probability, Educational Experiments