The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Agent-based modeling and simulation
Abstract
Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, mitigating the threat of bio-warfare, and understanding the factors that may be responsible for the fall of ancient civilizations. Such progress suggests the potential of ABMS to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use agent-based models as electronic laboratories. Some contend that ABMS ¿is a third way of doing science¿ and could augment traditional deductive and inductive reasoning as discovery methods. This brief tutorial introduces agent-based modeling by describing the foundations of ABMS, discussing some illustrative applications, and addressing toolkits and methods for developing agent-based models.
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Cites
(2000) · University of Maribor digital library (University of Maribor) · Cited by 9,354
Swarm Intelligence: From Natural to Artificial Systems
Bonabeau, E., Dorigo, M., & Theraulaz, G. (1999) · Oxford University Press eBooks · doi:10.1093/oso/9780195131581.001.0001 · Cited by 6,435
Agent-based modeling: Methods and techniques for simulating human systems
Bonabeau, E. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082080899 · Cited by 4,500
Growing Artificial Societies: Social Science from the Bottom Up
Epstein, J. M., & Axtell, R. L. (1996) · doi:10.7551/mitpress/3374.001.0001 · Cited by 2,441
Gardner, M. (1970) · Scientific American · doi:10.1038/scientificamerican1070-120 · Cited by 1,663
On agent-based software engineering
Jennings, N. R. (2000) · Artificial Intelligence · doi:10.1016/s0004-3702(99)00107-1 · Cited by 1,635
Hidden Order: How Adaptation Builds Complexity
Fukuyama, F., & Holland, J. H. (1996) · Foreign Affairs · doi:10.2307/20047667 · Cited by 1,130
The Swarm Simulation System: A Toolkit for Building Multi-Agent Simulations
Minar, N., Burkhart, R., Langton, C. G., & Askenazi, M. (1996) · Cited by 739
Experiences creating three implementations of the repast agent modeling toolkit
NORTH, M. J., Collier, N. T., & Vos, J. R. (2006) · ACM Transactions on Modeling and Computer Simulation · doi:10.1145/1122012.1122013 · Cited by 678
Self-citationAdvancing the Art of Simulation in the Social Sciences
Axelrod, R. (1997) · Lecture Notes in Economics and Mathematical Systems · doi:10.1007/978-3-662-03366-1_2 · Cited by 648
Cited by
Schleich, K., Warnken, U., Fricker, N., Öztürk, S., Richter, P., Kammerer, K., Schnölzer, M., Krammer, P. H., & Lavrik, I. N. (2012) · Molecular Cell · doi:10.1016/j.molcel.2012.05.006 · Cited by 198
Richter, M. A., Hagenmaier, M., Bandte, O., Parida, V., & Wincent, J. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121857 · Cited by 124
Multi-agent systems powered by large language models: applications in swarm intelligence
Jimenez-Romero, C., Yegenoglu, A., & Blum, C. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1593017 · Cited by 55
Cyberspace: A Digital Ecosystem
Lippert, K. J., & Cloutier, R. (2021) · Systems · doi:10.3390/systems9030048 · Cited by 32
Characterisation of academic journals in the digital age
Gu, X., & Blackmore, K. (2017) · Scientometrics · doi:10.1007/s11192-016-2219-4 · Cited by 29
Metadata
- Authors
- Macal, C. M., & North, M. J.
- Venue
- Proceedings of the 2009 Winter Simulation Conference (WSC)
- Publisher
- IEEE
- Published
- 2009-12
- Pages
- 86-98
- ISSN
- 0891-7736 (ISSN-L)
- OpenAlex
- W3140951851
- Cited by
- 517
- References
- 24
- FWCI
- 49.50
- Type
- conference paper
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
