The DOI matches its Crossref record; 80 of the 83 references it cites were found in a registry or an index.
On agent-based modeling and computational social science
Open accessAbstract
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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“Yet ABMs are often criticized for failing to capture the full spectrum of human behaviors (38). For example, conventional agents within ABMs do not use language, interpret social contexts, or engage in conversations with each other (39).”
From Can Generative AI improve social science? (2024) · cites this paper as [38]
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Cites
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“Examples of this application of ABM abound and are among the best cited works so far worked out in this field. phenomena trace back to as early as 1971, when the famous (Schelling, 1971) model of segregation was published in the Journal of Mathematical Sociology.”
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3 of the 83 references couldn’t be matched to a known paper.
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Boccignone, G., & Cordeschi, R. (2015) · Frontiers in Psychology · doi:10.3389/fpsyg.2015.00213 · Cited by 3
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BackgroundInfluentialAgent-based simulation and child protection systems: Rationale, implementation, and verification
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“Nevertheless, a major problem in ABM to model human behaviors was to design large-scale simulations [7].”
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Limitations in creating artificial populations in agent-based epidemic modeling: a systematic review
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Along the Border: An Agent-based Model of Migration along the United States- Mexico Border
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“This can add another layer of challenges in understanding this trend in migration, given that migrants from each country are facing unique push factors (Correa-Cabrera 2014).”
BackgroundModelling transformative adaptation: Case of post-earthquake Lyttelton, New Zealand
Ajulo, O. M., Asgary, A., Tang, P., & von Meding, J. K. (2021) · Environmental Science & Policy · doi:10.1016/j.envsci.2021.09.006 · Cited by 2
Magalhães, B. T., Lourenço, A. M. G., & Azevedo, N. F. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz149 · Cited by 2
Artificial Populations in Agent-Based ModelingPreprint
Glushchenko, O. E., Manolov, A., Kozlov, I., Tsurkis, V. I., Maslova, I., Popov, N., Samoilov, A., Lukashev, A., & Ilina, E. N. (2023) · Preprints.org · doi:10.20944/preprints202312.0346.v1 · Cited by 2
Social intelligence: How to integrate research? A mechanistic perspective
Miłkowski, M. (2017) · AI & Society · doi:10.1007/s00146-017-0787-3 · Cited by 2
“Such abilities can be described on various levels of abstraction, for example in agent-based models (Squazzoni 2012; Conte and Paolucci 2014).”
BackgroundA Generalized Network Generation Approach for Agent-Based Models
Hesz, K., Himmelspach, J., Reinhardt, O., & Uhrmacher, A. M. (2021) · Winter Simulation Conference · doi:10.1109/wsc52266.2021.9715377 · Cited by 1
“Since then, several papers have discussed the KIDS approach and the need for more realistic models to leverage the strengths of ABM to analyze external and internal mechanisms (Pastrav and Dignum (2020); Kraan et al. (2019); Conte and Paolucci (2014)).”
BackgroundAgent-Based Software Engineering, Paradigm Shift, or Research Program Evolution
Wautelet, Y., Schınckus, C., & Kolp, M. (2020) · IGI Global eBooks · doi:10.4018/978-1-7998-3016-0.ch073 · Cited by 1
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“Finally, as normative MAS based approaches being generative, we can easily establish the causality for specific incentive mechanisms and community emergence [13, 22].”
Theodoropoulos, G. K., Kennedy, C., Lee, P., Skelcher, C., Ferrari, E., & Sorge, V. (2023) · Springer eBooks · doi:10.1007/978-3-031-27986-7_29 · Cited by 1
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Larson, J. R., Cornell, C. A., & Aramovich, N. P. (2024) · Basic and Applied Social Psychology · doi:10.1080/01973533.2024.2313533 · Cited by 1
“Surprisingly, despite the growing number of helpful guides for developing ABMs (e.g., Conte & Paolucci, 2014; Eberlen et al., 2017; Grahek, et al., 2021; Jackson et al., 2017; Smaldino, 2020, 2023; van Rooij & Baggio, 2021), relatively little advice has heretofore been offered for how to…”
BackgroundModelling the future of meat consumption in Poland: an agent-based approach
Hezaveh, S. A., Adamczyk, D., Stasiuk, K., & Maison, D. A. (2024) · British Food Journal · doi:10.1108/bfj-01-2024-0055 · Cited by 1
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Lettieri, N., & Pica, I. (2025) · Oñati Socio-legal Series · doi:10.35295/osls.iisl.2311 · Cited by 1
“Conte and Paolucci (2014) identify three primary functions of ABMs, which can be used at the same time as: - Operational platforms for transforming theoretical frameworks into formalized, testable hypotheses; - Experimental laboratories for systematically testing theories and exploring…”
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Increasing Evacuation during Disaster Events
Kuhlman, C. J., Marathe, A., Vullikanti, A. K. S., Halim, N., & Mozumder, P. (2020) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/yjlt5649 · Cited by 1
“There have been many studies in the literature on the topic of evacuation, some of which use statistical models [7, 23, 24], while others use parameterized methods [4, 9, 17] and ABMs [12, 16, 27, 29, 34, 36].”
BackgroundCornacchione, E. B., & Reginato, L. (2022) · Advances in Scientific and Applied Accounting · doi:10.14392/asaa.2021140306 · Cited by 1
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BackgroundEquation-Free Computations as DDDAS Protocols for Bifurcation Studies: A Granular Chain Example
Williams, M. O., Psarellis, Y. M., Pozharskiy, D., Chong, C., Li, F., Yang, J., Kevrekidis, P. G., & Kevrekidis, I. G. (2023) · Springer eBooks · doi:10.1007/978-3-031-27986-7_5 · Cited by 1
Bora, Ş., Ünüvar, G. C., & Emek, S. (2019) · DergiPark (Istanbul University) · Cited by 1
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Navarro-Meneses, F. J. (2020) · Journal of Creating Value · doi:10.1177/2394964320961903 · Cited by 1
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Agent-Based Complex Systems Science in the Era of Global Sustainability CrisisPreprint
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Metadata
- Authors
- Conte, R., & Paolucci, M.
- Affiliations
- National Research Council (IT)
- Corresponding author
- Paolucci, Mario
- ORCID
- Paolucci, Mario
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2014-07-14
- Volume
- 5
- Pages
- 668-668
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC4094840
- OpenAlex
- W3124521395
- Cited by
- 160
- References
- 83
- Citations by year
- 2026: 12 · 2025: 15 · 2024: 17 · 2023: 15 · 2022: 12 · 2021: 17 · 2020: 20 · 2019: 9 · 2018: 12 · 2017: 11 · 2016: 8 · 2015: 7 · 2014: 2
- FWCI
- 9.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- European Commission (284709)
- Programma Operativo Nazionale Ricerca e Competitività (2007-2013)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy of Biology and Scientific Explanation
- Keywords
- agent-based modeling, computational social science, generative theory, generative power, cognitive models, interdisciplinary research, quantitative social science
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