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Quantum Circuit Components for Cognitive Decision-Making

This paper demonstrates that some non-classical models of human decision-making can be run successfully as circuits on quantum computers. Since the 1960s, many observed cognitive behaviors have been shown to violate rules based on classical probability and set theory. For example, the order in which...

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Autores principales: Widdows, Dominic, Rani, Jyoti, Pothos, Emmanuel M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138279/
https://www.ncbi.nlm.nih.gov/pubmed/37190336
http://dx.doi.org/10.3390/e25040548
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author Widdows, Dominic
Rani, Jyoti
Pothos, Emmanuel M.
author_facet Widdows, Dominic
Rani, Jyoti
Pothos, Emmanuel M.
author_sort Widdows, Dominic
collection PubMed
description This paper demonstrates that some non-classical models of human decision-making can be run successfully as circuits on quantum computers. Since the 1960s, many observed cognitive behaviors have been shown to violate rules based on classical probability and set theory. For example, the order in which questions are posed in a survey affects whether participants answer ‘yes’ or ‘no’, so the population that answers ‘yes’ to both questions cannot be modeled as the intersection of two fixed sets. It can, however, be modeled as a sequence of projections carried out in different orders. This and other examples have been described successfully using quantum probability, which relies on comparing angles between subspaces rather than volumes between subsets. Now in the early 2020s, quantum computers have reached the point where some of these quantum cognitive models can be implemented and investigated on quantum hardware, by representing the mental states in qubit registers, and the cognitive operations and decisions using different gates and measurements. This paper develops such quantum circuit representations for quantum cognitive models, focusing particularly on modeling order effects and decision-making under uncertainty. The claim is not that the human brain uses qubits and quantum circuits explicitly (just like the use of Boolean set theory does not require the brain to be using classical bits), but that the mathematics shared between quantum cognition and quantum computing motivates the exploration of quantum computers for cognition modeling. Key quantum properties include superposition, entanglement, and collapse, as these mathematical elements provide a common language between cognitive models, quantum hardware, and circuit implementations.
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spelling pubmed-101382792023-04-28 Quantum Circuit Components for Cognitive Decision-Making Widdows, Dominic Rani, Jyoti Pothos, Emmanuel M. Entropy (Basel) Article This paper demonstrates that some non-classical models of human decision-making can be run successfully as circuits on quantum computers. Since the 1960s, many observed cognitive behaviors have been shown to violate rules based on classical probability and set theory. For example, the order in which questions are posed in a survey affects whether participants answer ‘yes’ or ‘no’, so the population that answers ‘yes’ to both questions cannot be modeled as the intersection of two fixed sets. It can, however, be modeled as a sequence of projections carried out in different orders. This and other examples have been described successfully using quantum probability, which relies on comparing angles between subspaces rather than volumes between subsets. Now in the early 2020s, quantum computers have reached the point where some of these quantum cognitive models can be implemented and investigated on quantum hardware, by representing the mental states in qubit registers, and the cognitive operations and decisions using different gates and measurements. This paper develops such quantum circuit representations for quantum cognitive models, focusing particularly on modeling order effects and decision-making under uncertainty. The claim is not that the human brain uses qubits and quantum circuits explicitly (just like the use of Boolean set theory does not require the brain to be using classical bits), but that the mathematics shared between quantum cognition and quantum computing motivates the exploration of quantum computers for cognition modeling. Key quantum properties include superposition, entanglement, and collapse, as these mathematical elements provide a common language between cognitive models, quantum hardware, and circuit implementations. MDPI 2023-03-23 /pmc/articles/PMC10138279/ /pubmed/37190336 http://dx.doi.org/10.3390/e25040548 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Widdows, Dominic
Rani, Jyoti
Pothos, Emmanuel M.
Quantum Circuit Components for Cognitive Decision-Making
title Quantum Circuit Components for Cognitive Decision-Making
title_full Quantum Circuit Components for Cognitive Decision-Making
title_fullStr Quantum Circuit Components for Cognitive Decision-Making
title_full_unstemmed Quantum Circuit Components for Cognitive Decision-Making
title_short Quantum Circuit Components for Cognitive Decision-Making
title_sort quantum circuit components for cognitive decision-making
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10138279/
https://www.ncbi.nlm.nih.gov/pubmed/37190336
http://dx.doi.org/10.3390/e25040548
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