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Learning under constraints: a theoretical framework for comparing resource-constrained learning in biological and artificial systems.

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Title: Learning under constraints: a theoretical framework for comparing resource-constrained learning in biological and artificial systems.
Authors: Kucherov, Dmytro1, dmytro.kucherov@npp.kai.edu.ua, Dolgikh, Serge2, dmytro.kucherov@npp.kai.edu.ua, Podelskyi, Serhii1
Source: Frontiers in Computational Neuroscience; 2026, p1-17, 17p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 194994016
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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      – Type: doi
        Value: 10.3389/fncom.2026.1636604
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      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 1
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      – TitleFull: Learning under constraints: a theoretical framework for comparing resource-constrained learning in biological and artificial systems.
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            NameFull: Dolgikh, Serge
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            – D: 01
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              Text: 2026
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              Y: 2026
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