Modeling absolute and relative familiarity through Hebbian and anti-Hebbian learning rules

Warnier, William; Read, John; Delhaye, Emma; Sougné, Jacques

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Modeling absolute and relative familiarity through Hebbian and anti-Hebbian learning rules

Warnier, William; Read, John; Delhaye, Emma et al.

2025 • RFN Conference 2025

Editorial reviewed

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https://hdl.handle.net/2268/332206

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Keywords :

familiarity; artificial neural network; model

Abstract :

[en] This project aims at modeling different type of familiarity through different learning rules in an artificial neural network.

Disciplines :

Theoretical & cognitive psychology

Author, co-author :

Warnier, William ; Université de Liège - ULiège > Faculté de Psychologie, Logopédie et Sciences de l'Education > Master sc. psycho., fin. spéc.

Read, John ; Université de Liège - ULiège > GIGA

Delhaye, Emma ; Université de Liège - ULiège > GIGA > GIGA Neurosciences - Aging & Memory ; University of Lisbon > Faculty of Psychology > CICPSI

Sougné, Jacques ; Université de Liège - ULiège > UDI FPLSE

Language :

English

Title :

Modeling absolute and relative familiarity through Hebbian and anti-Hebbian learning rules

Publication date :

15 April 2025

Event name :

RFN Conference 2025

Event organizer :

Christine Bastin, Uliège
Olivier Luminet, UCLouvain

Event date :

15th and 16th of April 2025

Audience :

International

Peer review/Selection committee :

Editorial reviewed

Available on ORBi :

since 23 May 2025

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