Understanding attention: in minds and machines

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dc.contributor.author Sawant, Shriraj P.
dc.contributor.author Singh, Shruti
dc.date.accessioned 2020-12-17T09:06:02Z
dc.date.available 2020-12-17T09:06:02Z
dc.date.issued 2020-12
dc.identifier.citation Sawant, Shriraj P. and Singh, Shruti,"Understanding attention: in minds and machines", arXiv, Cornell University Library, DOI: arXiv:/2012.02659, Dec. 2020. en_US
dc.identifier.uri http://arxiv.org/abs/2012.02659
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/6138
dc.description.abstract Attention is a complex and broad concept, studied across multiple disciplines spanning artificial intelligence, cognitive science, psychology, neuroscience, and related fields. Although many of the ideas regarding attention do not significantly overlap among these fields, there is a common theme of adaptive control of limited resources. In this work, we review the concept and variants of attention in artificial neural networks (ANNs). We also discuss the origin of attention from the neuroscience point of view parallel to that of ANNs. Instead of having seemingly disconnected dialogues between varied disciplines, we suggest grounding the ideas on common conceptual frameworks for a systematic analysis of attention and towards possible unification of ideas in AI and Neuroscience
dc.description.statementofresponsibility by Shriraj P. Sawant and Shruti Singh
dc.language.iso en_US en_US
dc.publisher Cornell University Library en_US
dc.subject Artificial Intelligence (cs.AI) en_US
dc.subject Machine Learning (cs.LG) en_US
dc.subject Neural en_US
dc.subject Evolutionary Computing (cs.NE) en_US
dc.title Understanding attention: in minds and machines en_US
dc.type Pre-Print en_US
dc.relation.journal arXiv


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