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Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition

A probabilistic graphical model, Neuronal Unit of Thoughts (NUTs), is proposed in this paper that offers a formalism for the integration of lower-level cognitions. Nodes or neurons in NUTs represent sensory data or mental concepts or actions, and edges the causal relation between them. A node affec...

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Main Author: Zakaria, N.
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2021
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111964038&doi=10.1007%2f978-981-16-1089-9_66&partnerID=40&md5=3a0cb4771da002d950ef2819caf30f07
http://eprints.utp.edu.my/29472/
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spelling my.utp.eprints.294722022-03-25T02:07:26Z Neuronal Unit of Thoughts (NUTs); A Probabilistic Formalism for Higher-Order Cognition Zakaria, N. A probabilistic graphical model, Neuronal Unit of Thoughts (NUTs), is proposed in this paper that offers a formalism for the integration of lower-level cognitions. Nodes or neurons in NUTs represent sensory data or mental concepts or actions, and edges the causal relation between them. A node affects a change in the Action Potential (AP) of its child node, triggering a value change once the AP reaches a fuzzy threshold. Multiple NUTs may be crossed together producing a novel NUTs. The transition time in a NUTs, in response to a �surprise,� is characterized, and the formalism is evaluated in the context of a non-trivial application: Autonomous Driving with imperfect sensors. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Springer Science and Business Media Deutschland GmbH 2021 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111964038&doi=10.1007%2f978-981-16-1089-9_66&partnerID=40&md5=3a0cb4771da002d950ef2819caf30f07 Zakaria, N. (2021) Neuronal Unit of Thoughts (NUTs); A Probabilistic Formalism for Higher-Order Cognition. Lecture Notes in Networks and Systems, 204 . pp. 855-871. http://eprints.utp.edu.my/29472/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description A probabilistic graphical model, Neuronal Unit of Thoughts (NUTs), is proposed in this paper that offers a formalism for the integration of lower-level cognitions. Nodes or neurons in NUTs represent sensory data or mental concepts or actions, and edges the causal relation between them. A node affects a change in the Action Potential (AP) of its child node, triggering a value change once the AP reaches a fuzzy threshold. Multiple NUTs may be crossed together producing a novel NUTs. The transition time in a NUTs, in response to a �surprise,� is characterized, and the formalism is evaluated in the context of a non-trivial application: Autonomous Driving with imperfect sensors. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
format Article
author Zakaria, N.
spellingShingle Zakaria, N.
Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
author_facet Zakaria, N.
author_sort Zakaria, N.
title Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
title_short Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
title_full Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
title_fullStr Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
title_full_unstemmed Neuronal Unit of Thoughts (NUTs); AÂ Probabilistic Formalism for Higher-Order Cognition
title_sort neuronal unit of thoughts (nuts); aâ probabilistic formalism for higher-order cognition
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85111964038&doi=10.1007%2f978-981-16-1089-9_66&partnerID=40&md5=3a0cb4771da002d950ef2819caf30f07
http://eprints.utp.edu.my/29472/
_version_ 1738656970617913344
score 13.223943

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