Agent-based modeling: Methods and techniques for simulating human systems
Open accessAbstract
Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed.
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The model is useful to explain groupthink phenomena by confirming and clarifying existing findings based on assumptions on the micro level, i.e., capturing emergent phenomena.
“The model has been proven to be useful to explain groupthink phenomena by confirming and clarifying existing findings based on assumptions on the micro level i.e. capturing emergent phenomena [6].”
From Closed-mindedness and insulation in groupthink: their effects and the devil’s advocacy as a preventive measure (2021) · cites this paper as [6]
The passage labeled Abstract (page not provided) says agent-based modeling can capture emergent group behavior from individual-level rules. It does not establish that the cited paper's model explains groupthink specifically or has been proven to confirm and clarify existing findings about it. (LLM, conf=0.85)
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“…acknowledgment, when the proceedings of a Sackler Colloqium of the National Academy of Sciences, under the title “Adaptive Agents, Intelligence, and Emergent Human Organization: Capturing Complexity through Agent-Based Modeling,” held in October 2001, were published on PNAS (Bonabeau, 2002).”
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- Authors
- Bonabeau, E.
- Affiliations
- Icosystem (United States) (US)
- Corresponding author
- Bonabeau, Eric
- ORCID
- Bonabeau, Eric
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2002-05-14
- Volume
- 99
- Issue
- suppl_3
- Pages
- 7280-7287
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC128598
- OpenAlex
- W2150704630
- Cited by
- 4,500
- References
- 12
- Citations by year
- 2026: 209 · 2025: 215 · 2024: 247 · 2023: 283 · 2022: 279 · 2021: 314 · 2020: 286 · 2019: 279 · 2018: 254 · 2017: 263 · 2016: 244 · 2015: 252 · 2014: 258 · 2013: 248 · 2012: 223
- FWCI
- 26.88
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Social Sciences › Decision Sciences › Management Science and Operations Research › Complex Systems and Decision Making
- Keywords
- agent-based modeling, business applications, flow simulation, organizational simulation, market simulation, diffusion simulation
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