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Rey, Arnaud; Fagot, Joël; Mathy, Fabien; Lazartigues, Laura; Tosatto, Laure; Bonafos, Guillem; Freyermuth, Jean-Marc; Lavigne, Frédéric – Cognitive Science, 2022
The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus…
Descriptors: Animals, Learning Processes, Associative Learning, Serial Learning
Erdin Mujezinovic; Vsevolod Kapatsinski; Ruben van de Vijver – Cognitive Science, 2024
A word often expresses many different morphological functions. Which part of a word contributes to which part of the overall meaning is not always clear, which raises the question as to how such functions are learned. While linguistic studies tacitly assume the co-occurrence of cues and outcomes to suffice in learning these functions (Baer-Henney,…
Descriptors: Morphology (Languages), Phonology, Morphemes, Cues
Kachergis, George; Yu, Chen; Shiffrin, Richard M. – Cognitive Science, 2017
Prior research has shown that people can learn many nouns (i.e., word--object mappings) from a short series of ambiguous situations containing multiple words and objects. For successful cross-situational learning, people must approximately track which words and referents co-occur most frequently. This study investigates the effects of allowing…
Descriptors: Vocabulary Development, Linguistic Theory, Context Effect, Familiarity
Stevens, Jon Scott; Gleitman, Lila R.; Trueswell, John C.; Yang, Charles – Cognitive Science, 2017
We evaluate here the performance of four models of cross-situational word learning: two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed "Pursuit," uses an associative…
Descriptors: Semantics, Associative Learning, Probability, Computational Linguistics
Escudero, Paola; Mulak, Karen E.; Vlach, Haley A. – Cognitive Science, 2016
"Cross-situational statistical learning" of words involves tracking co-occurrences of auditory words and objects across time to infer word-referent mappings. Previous research has demonstrated that learners can infer referents across sets of very phonologically distinct words (e.g., WUG, DAX), but it remains unknown whether learners can…
Descriptors: Statistics, Learning Processes, Oral Language, Vocabulary Development
Veksler, Vladislav D.; Gray, Wayne D.; Schoelles, Michael J. – Cognitive Science, 2013
Reinforcement learning (RL) models of decision-making cannot account for human decisions in the absence of prior reward or punishment. We propose a mechanism for choosing among available options based on goal-option association strengths, where association strengths between objects represent previously experienced object proximity. The proposed…
Descriptors: Proximity, Decision Making, Goal Orientation, Cognitive Processes
Yu, Chen; Ballard, Dana H.; Aslin, Richard N. – Cognitive Science, 2005
We examine the influence of inferring interlocutors' referential intentions from their body movements at the early stage of lexical acquisition. By testing human participants and comparing their performances in different learning conditions, we find that those embodied intentions facilitate both word discovery and word-meaning association. In…
Descriptors: Language Acquisition, Testing, Comparative Analysis, Learning Processes