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NeuroQuantologyVolume 17, Issue 1, January 2019, Pages 72-96

Quantum metalanguage and the new cognitive synthesis(Article)(Open Access)

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  • aUral Federal University, Mira str. 19, Yekaterinburg, 620002, Russian Federation
  • bInternational Center for Mathematical Modelling in Physics and Cognitive Sciences, Linnaeus University, Växjö, S-35195, Sweden
  • cNational Research University of Information Technologies, Mechanics and Optics (ITMO), St. Petersburg, 197101, Russian Federation
  • dComputer Engineering and Computer Science Speed School of Engineering, University of Louisville, United States

Abstract

Problems with mechanisms of thinking and cognition in many ways remain unresolved. Why are a priori inferences possible? Why can a human understand but a computer cannot? It has been shown that when creating new concepts, generalization is contradictory in the sense that to be created concepts must exist a priori, and therefore, they are not new. The process of knowledge acquisition is also contradictory, as it inevitably involves recognition, which can be realized only when there is an a priori standard. Known approaches of the framework of artificial intelligence (in particular, Bayesian) do not determine the origins of knowledge, as these approaches are effective only when “good” hypotheses are made. The formation of “good” hypotheses must occur a priori. To address these issues and paradoxes, a fundamentally new approach to problems of cognition that is based on completely innate behavioral programs is proposed. The process of cognition within the framework of the concept of a quantum metalanguage involves the selection of adequate a priori existing (innate) programs (logical variables and rules for working with them) that are most adequate to a given situation. The quantum properties of this metalanguage are necessary to implement such programs. © 2019, Anka Publishers. All rights reserved.

Author keywords

Chinese roomGeneralizationKnowledge acquisitionMetalanguageQuantum decision makingUnderstanding

Indexed keywords

EMTREE medical terms:articleartificial intelligencedecision makinghumanhuman experimentlearningsynthesis
  • ISSN: 13035150
  • Source Type: Journal
  • Original language: English
  • DOI: 10.14704/nq.2019.17.1.1904
  • Document Type: Article
  • Publisher: Anka Publishers

  Melkikh, A.V.; Ural Federal University, Mira str. 19, Yekaterinburg, Russian Federation;
© Copyright 2019 Elsevier B.V., All rights reserved.

Cited by 6 documents

Melkikh, A.V.
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(2023) BioSystems
Surov, I.A. , Semenenko, E. , Platonov, A.V.
Quantum semantics of text perception
(2021) Scientific Reports
Melkikh, A.V.
The brain and the new foundations of mathematics
(2021) Symmetry
View details of all 6 citations
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