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On the Problem of Small Objects

We discuss how to assess computationally the aesthetic value of “small” objects, namely those that have short digital descriptions. Such small objects still matter: they include headlines, poems, song lyrics, short musical scripts and other culturally crucial items. Yet, small objects are a confound...

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Detalles Bibliográficos
Autores principales: Brown, Daniel G., Mondol, Tiasa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8620042/
https://www.ncbi.nlm.nih.gov/pubmed/34828222
http://dx.doi.org/10.3390/e23111524
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author Brown, Daniel G.
Mondol, Tiasa
author_facet Brown, Daniel G.
Mondol, Tiasa
author_sort Brown, Daniel G.
collection PubMed
description We discuss how to assess computationally the aesthetic value of “small” objects, namely those that have short digital descriptions. Such small objects still matter: they include headlines, poems, song lyrics, short musical scripts and other culturally crucial items. Yet, small objects are a confounding case for our recent work adapting ideas from algorithmic information theory (AIT) to the domain of computational creativity, as they cannot be either logically deep or sophisticated following the traditional definitions of AIT. We show how restricting the class of models under analysis can make it the case that we can still separate high-quality small objects from ordinary ones, and discuss the strengths and limitations of our adaptation.
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spelling pubmed-86200422021-11-27 On the Problem of Small Objects Brown, Daniel G. Mondol, Tiasa Entropy (Basel) Article We discuss how to assess computationally the aesthetic value of “small” objects, namely those that have short digital descriptions. Such small objects still matter: they include headlines, poems, song lyrics, short musical scripts and other culturally crucial items. Yet, small objects are a confounding case for our recent work adapting ideas from algorithmic information theory (AIT) to the domain of computational creativity, as they cannot be either logically deep or sophisticated following the traditional definitions of AIT. We show how restricting the class of models under analysis can make it the case that we can still separate high-quality small objects from ordinary ones, and discuss the strengths and limitations of our adaptation. MDPI 2021-11-16 /pmc/articles/PMC8620042/ /pubmed/34828222 http://dx.doi.org/10.3390/e23111524 Text en © 2021 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
Brown, Daniel G.
Mondol, Tiasa
On the Problem of Small Objects
title On the Problem of Small Objects
title_full On the Problem of Small Objects
title_fullStr On the Problem of Small Objects
title_full_unstemmed On the Problem of Small Objects
title_short On the Problem of Small Objects
title_sort on the problem of small objects
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8620042/
https://www.ncbi.nlm.nih.gov/pubmed/34828222
http://dx.doi.org/10.3390/e23111524
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