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Title: Emulating Cued Recall of Abstract Concepts via Regulated Activation Networks
Authors: Sharma, Rahul 
Ribeiro, Bernardete 
Pinto, Alexandre Miguel 
Cardoso, Amílcar 
Keywords: Computational psychology; Computational cognitive modeling; Machine learning; Concept blending; Conceptual combinations; Recall; Computational creativity
Issue Date: 2021
Publisher: MDPI
Project: info:eu-repo/grantAgreement/EC/FP7/611733/EU/Concept Creation Technology 
Serial title, monograph or event: Applied Sciences
Volume: 11
Issue: 5
Place of publication or event: Basel, Switzerland
Abstract: Abstract concepts play a vital role in decision-making or recall operations because the associations among them are essential for contextual processing. Abstract concepts are complex and difficult to represent (conceptually, formally, or computationally), leading to difficulties in their comprehension and recall. This contribution reports the computational simulation of the cued recall of abstract concepts by exploiting their learned associations. The cued recall operation is realized via a novel geometric back-propagation algorithm that emulates the recall of abstract concepts learned through regulated activation network (RAN) modeling. During recall operation, another algorithm uniquely regulates the activation of concepts (nodes) by injecting excitatory, neutral, and inhibitory signals to other concepts of the same level. A Toy-data problem is considered to illustrate the RAN modeling and recall procedure. The results display how regulation enables contextual awareness among abstract nodes during the recall process. The MNIST dataset is used to show how recall operations retrieve intuitive and non-intuitive blends of abstract nodes. We show that every recall process converges to an optimal image. With more cues, better images are recalled, and every intermediate image obtained during the recall iterations corresponds to the varying cognitive states of the recognition procedure.
ISSN: 2076-3417
DOI: 10.3390/app11052134
Rights: openAccess
Appears in Collections:I&D CISUC - Artigos em Revistas Internacionais

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