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Perkins, Laurel; Feldman, Naomi H.; Lidz, Jeffrey – Cognitive Science, 2022
Learning in any domain depends on how the data for learning are represented. In the domain of language acquisition, children's representations of the speech they hear determine what generalizations they can draw about their target grammar. But these input representations change over development as a function of children's developing linguistic…
Descriptors: Persuasive Discourse, Language Acquisition, Form Classes (Languages), Verbs
Jarecki, Jana B.; Meder, Björn; Nelson, Jonathan D. – Cognitive Science, 2018
Humans excel in categorization. Yet from a computational standpoint, learning a novel probabilistic classification task involves severe computational challenges. The present paper investigates one way to address these challenges: assuming class-conditional independence of features. This feature independence assumption simplifies the inference…
Descriptors: Classification, Conditioning, Inferences, Novelty (Stimulus Dimension)
Piantadosi, Steven T.; Tenenbaum, Joshua B.; Goodman, Noah D. – Cognition, 2012
In acquiring number words, children exhibit a qualitative leap in which they transition from understanding a few number words, to possessing a rich system of interrelated numerical concepts. We present a computational framework for understanding this inductive leap as the consequence of statistical inference over a sufficiently powerful…
Descriptors: Statistical Inference, Number Concepts, Models, Computation
Rips, Lance J.; Asmuth, Jennifer; Bloomfield, Amber – Cognition, 2008
According to one theory about how children learn the meaning of the words for the positive integers, they first learn that "one," "two," and "three" stand for appropriately sized sets. They then conclude by inductive inference that the next numeral in the count sequence denotes the size of sets containing one more object than the size denoted by…
Descriptors: Learning Strategies, Logical Thinking, Number Concepts, Inferences
Lee, Michael D.; Vanpaemel, Wolf – Cognitive Science, 2008
This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that considers an existing model of category representation, the Varying Abstraction Model (VAM), which attempts to infer the representations people use from their behavior in…
Descriptors: Computation, Inferences, Cognitive Science, Models
Juliusson, Asgeir; Gamble, Amelie; Garling, Tommy – Journal of Experimental Psychology Applied, 2005
In European countries, field studies investigate how citizens acquire knowledge of the new currency, the euro. In 3 laboratory experiments, the authors recruited 168 undergraduates to examine whether such accurate knowledge is acquired from learning prices in the new currency. The results show fast learning of prices of duration of cellular phone…
Descriptors: Foreign Countries, Inferences, Field Studies, Computation

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