The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Tutorial on agent-based modelling and simulation
Abstract
Agent-based modelling and simulation (ABMS) is a relatively new approach to modelling systems composed of autonomous, interacting agents. Agent-based modelling is a way to model the dynamics of complex systems and complex adaptive systems. Such systems often self-organize themselves and create emergent order. Agent-based models also include models of behaviour (human or otherwise) and are used to observe the collective effects of agent behaviours and interactions. The development of agent modelling tools, the availability of micro-data, and advances in computation have made possible a growing number of agent-based applications across a variety of domains and disciplines. This article provides a brief introduction to ABMS, illustrates the main concepts and foundations, discusses some recent applications across a variety of disciplines, and identifies methods and toolkits for developing agent models.
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Citations
Cites
The Origins of Order: Self-Organization and Selection in Evolution
Kauffman, S. A. (1993) · doi:10.1093/oso/9780195079517.001.0001 · Cited by 7,855
The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration
Axelrod, R. (1997) · doi:10.1515/9781400822300 · Cited by 1,759
Yin, L. (2007) · Journal of Regional Analysis & Policy · doi:10.68479/001c.9304 · Cited by 11
Cited by
Caro, J. J., Briggs, A. H., Siebert, U., & Kuntz, K. M. (2012) · Medical Decision Making · doi:10.1177/0272989x12454577 · Cited by 520
Everything you need to know about agent-based modelling and simulation
Macal, C. M. (2016) · Journal of Simulation · doi:10.1057/jos.2016.7 · Cited by 469
Self-citationEmergency medical services and beyond: Addressing new challenges through a wide literature review
Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. T. (2017) · Computers & Operations Research · doi:10.1016/j.cor.2016.09.016 · Cited by 339
Rai, V., & Robinson, S. A. (2015) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2015.04.014 · Cited by 335
Advancing microbial sciences by individual-based modelling
Hellweger, F. L., Clegg, R. J., Clark, J. R., Plugge, C. M., & Kreft, J.-U. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.62 · Cited by 202
Metadata
- Authors
- Macal, C. M., & North, M. J.
- Venue
- Journal of Simulation
- Publisher
- Informa UK Limited
- Published
- 2010-09
- Volume
- 4
- Issue
- 3
- Pages
- 151-162
- ISSN
- 1747-7778 (ISSN-L)
- 1747-7786
- OpenAlex
- W3011439212
- Cited by
- 1,710
- References
- 3
- FWCI
- 94.20
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
