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On agent-based modeling and computational social science

In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the genera...

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Detalles Bibliográficos
Autores principales: Conte, Rosaria, Paolucci, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4094840/
https://www.ncbi.nlm.nih.gov/pubmed/25071642
http://dx.doi.org/10.3389/fpsyg.2014.00668
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author Conte, Rosaria
Paolucci, Mario
author_facet Conte, Rosaria
Paolucci, Mario
author_sort Conte, Rosaria
collection PubMed
description In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.
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spelling pubmed-40948402014-07-28 On agent-based modeling and computational social science Conte, Rosaria Paolucci, Mario Front Psychol Psychology In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS. Frontiers Media S.A. 2014-07-14 /pmc/articles/PMC4094840/ /pubmed/25071642 http://dx.doi.org/10.3389/fpsyg.2014.00668 Text en Copyright © 2014 Conte and Paolucci. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Conte, Rosaria
Paolucci, Mario
On agent-based modeling and computational social science
title On agent-based modeling and computational social science
title_full On agent-based modeling and computational social science
title_fullStr On agent-based modeling and computational social science
title_full_unstemmed On agent-based modeling and computational social science
title_short On agent-based modeling and computational social science
title_sort on agent-based modeling and computational social science
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4094840/
https://www.ncbi.nlm.nih.gov/pubmed/25071642
http://dx.doi.org/10.3389/fpsyg.2014.00668
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