Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
A Picture is Worth 7.17 Words : Learning Categories from Examples and Definitions. / Moskvichev, Arseny ; Tikhonov, Roman ; Steyvers, Mark.
41st Annual Meeting of the Cognitive Science Society (CogSci 2019): Proceedings. Curran Associates, Inc. , 2019. p. 2406-2412.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
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TY - GEN
T1 - A Picture is Worth 7.17 Words
T2 - 41st Annual Meeting of the Cognitive Science Society
AU - Moskvichev, Arseny
AU - Tikhonov, Roman
AU - Steyvers, Mark
PY - 2019
Y1 - 2019
N2 - Both examples and verbal explanations play an important role in learning new concepts and categories. At the same time, learning from verbal explanations is not accounted for in most category learning models, and is not studied in the traditional category learning paradigm. We propose a rational category communication model that formally describes the process of communicating a category structure using both verbal explanations and visual examples in a pedagogical setting. We build our model based on the assumption that verbal instructions are best suited for communication of crude constraints on a category structure, while exemplars complement it by providing means for finer adjustments. Our empirical study demonstrates that verbal communication is indeed more robust to changes in stimuli dimensionality, but that its efficiency is adversely affected when distinguishing between categories requires perceptual precision. Communicating through examples has a reversed pattern. We hope that both the proposed experimental paradigm and the computational model would facilitate further research into the relative roles of verbal and exemplar communication in category learning.
AB - Both examples and verbal explanations play an important role in learning new concepts and categories. At the same time, learning from verbal explanations is not accounted for in most category learning models, and is not studied in the traditional category learning paradigm. We propose a rational category communication model that formally describes the process of communicating a category structure using both verbal explanations and visual examples in a pedagogical setting. We build our model based on the assumption that verbal instructions are best suited for communication of crude constraints on a category structure, while exemplars complement it by providing means for finer adjustments. Our empirical study demonstrates that verbal communication is indeed more robust to changes in stimuli dimensionality, but that its efficiency is adversely affected when distinguishing between categories requires perceptual precision. Communicating through examples has a reversed pattern. We hope that both the proposed experimental paradigm and the computational model would facilitate further research into the relative roles of verbal and exemplar communication in category learning.
KW - categorization
KW - category learning
KW - computational modelling
KW - communication channels
KW - communication efficiency
UR - http://www.proceedings.com/50152.html
M3 - Conference contribution
SN - 9781510891555
SP - 2406
EP - 2412
BT - 41st Annual Meeting of the Cognitive Science Society (CogSci 2019)
PB - Curran Associates, Inc.
Y2 - 24 July 2019 through 27 July 2019
ER -
ID: 49675274