Learning reference biases from language input: A cognitive modelling approach

Abigail Grace Toth*, Niels Taatgen, Petra Hendriks, Jacolien van Rij

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

94 Downloads (Pure)

Samenvatting

In order to gain insight into how people acquire certain reference biases in language and how those biases influence online language processing, we constructed a cognitive model and presented it with a dataset containing reference asymmetries. Via prediction and reinforcement learning, the model was able to pick up on the asymmetries in the input. The model predictions have implications for various accounts of reference processing and demonstrate that seemingly complex behavior can be explained by simple learning mechanisms
Originele taal-2English
TitelProceedings of the 19th International Conference on Cognitive Modelling (ICCM 2021)
RedacteurenTerrence C. Stewart
Plaats van productieUniversity Park, PA
UitgeverijApplied Cognitive Science Lab, Penn State
Pagina's282-288
Aantal pagina's7
ISBN van elektronische versie978-0-9985082-5-2
StatusPublished - 2021
EvenementInternational Conference on Cognitive Modeling 2021 - Online
Duur: 29-jun.-20219-jul.-2021
https://mathpsych.org/conference/7/schedule

Conference

ConferenceInternational Conference on Cognitive Modeling 2021
Verkorte titelICCM 2021
Periode29/06/202109/07/2021
Internet adres

Citeer dit