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Stimuli strategy and learning dynamics promote the wisdom of crowds

ABSTRACT: Collective wisdom is the ability of a group to perform more effectively than any individual alone. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that reinforcement learning stimulus may play the role in enhancing collective voting accuracy....

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Detalles Bibliográficos
Autores principales: Zhenpeng, Li, Xijin, Tang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696253/
https://www.ncbi.nlm.nih.gov/pubmed/34961810
http://dx.doi.org/10.1140/epjb/s10051-021-00259-9
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author Zhenpeng, Li
Xijin, Tang
author_facet Zhenpeng, Li
Xijin, Tang
author_sort Zhenpeng, Li
collection PubMed
description ABSTRACT: Collective wisdom is the ability of a group to perform more effectively than any individual alone. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that reinforcement learning stimulus may play the role in enhancing collective voting accuracy. And collective voting bias can be dismissed through self-reinforcing global cooperative learning. Numeric simulations suggest that the provided method can increase collective voting accuracy. We conclude that real-world systems might seek reward-based incentive mechanism as an alternative to surmount group decision error. GRAPHICAL ABSTRACT: [Image: see text]
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spelling pubmed-86962532021-12-23 Stimuli strategy and learning dynamics promote the wisdom of crowds Zhenpeng, Li Xijin, Tang Eur Phys J B Regular Article - Statistical and Nonlinear Physics ABSTRACT: Collective wisdom is the ability of a group to perform more effectively than any individual alone. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that reinforcement learning stimulus may play the role in enhancing collective voting accuracy. And collective voting bias can be dismissed through self-reinforcing global cooperative learning. Numeric simulations suggest that the provided method can increase collective voting accuracy. We conclude that real-world systems might seek reward-based incentive mechanism as an alternative to surmount group decision error. GRAPHICAL ABSTRACT: [Image: see text] Springer Berlin Heidelberg 2021-12-23 2021 /pmc/articles/PMC8696253/ /pubmed/34961810 http://dx.doi.org/10.1140/epjb/s10051-021-00259-9 Text en © The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Regular Article - Statistical and Nonlinear Physics
Zhenpeng, Li
Xijin, Tang
Stimuli strategy and learning dynamics promote the wisdom of crowds
title Stimuli strategy and learning dynamics promote the wisdom of crowds
title_full Stimuli strategy and learning dynamics promote the wisdom of crowds
title_fullStr Stimuli strategy and learning dynamics promote the wisdom of crowds
title_full_unstemmed Stimuli strategy and learning dynamics promote the wisdom of crowds
title_short Stimuli strategy and learning dynamics promote the wisdom of crowds
title_sort stimuli strategy and learning dynamics promote the wisdom of crowds
topic Regular Article - Statistical and Nonlinear Physics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8696253/
https://www.ncbi.nlm.nih.gov/pubmed/34961810
http://dx.doi.org/10.1140/epjb/s10051-021-00259-9
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