Cited by 507Multi-Agent Systems and NegotiationSimulation Techniques and ApplicationsPhilosophy and History of Science

How to build and use agent-based models in social science

Gilbert, Nigel, Terna, Pietro·2000·Mind & Society

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Registry

Crossref · 10.1007/bf02512229

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  • ABMs are the cornerstone of opinion dynamics simulation, defining mathematical rules for agents' opinion updates in response to messages.

    “Agent-Based Models (ABMs) are the cornerstone of opinion dynamics simulation, defining mathematical rules for agents' opinion updates in response to messages (Gilbert and Terna, 2000; Smaldino, 2023; Lorenz et al., 2021; Chuang and Rogers, 2023; Epstein, 2012; Flache et al., 2017).”

    From Simulating Opinion Dynamics with Networks of LLM-based Agents (2024) · cites this paper as Gilbert and Terna, 2000

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Authors
Gilbert, N., & Terna, P.
Affiliations
  • University of Surrey (GB)
  • University of Turin (IT)
Corresponding author
Terna, Pietro
Venue
Mind & Society
Published
2000-03
Volume
1
Issue
1
Pages
57-72
ISSN
  • 1593-7879 (ISSN-L)
  • 1860-1839
OpenAlex
W1978706036
Cited by
507
References
0
Citations by year
2026: 7 · 2025: 12 · 2024: 14 · 2023: 21 · 2022: 10 · 2021: 17 · 2020: 24 · 2019: 19 · 2018: 21 · 2017: 36 · 2016: 36 · 2015: 37 · 2014: 29 · 2013: 33 · 2012: 32
FWCI
5.83
Type
journal article
Language
en
Open access
closed
Locations
  • Mind & Society (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Surrey Research Insight Open Access (The University of Surrey) (submittedVersion)
  • Institutional Research Information System University of Turin (University of Turin) (submittedVersion)
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 and History of Science
Keywords
agent-based modeling, computer simulation, social science methodology, emergence, simulation debugging

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