volume 100 issue 10 pages 003754972110688

Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity

Publication typeJournal Article
Publication date2022-01-05
scimago Q2
wos Q3
SJR0.382
CiteScore3.8
Impact factor2.0
ISSN00375497, 17413133
Computer Graphics and Computer-Aided Design
Software
Modeling and Simulation
Abstract

Agent-based modeling is a simulation method in which autonomous agents interact with their environment and one another, given a predefined set of rules. It is an integral method for modeling and simulating complex systems, such as socio-economic problems. Since agent-based models are not described by simple and concise mathematical equations, the code that generates them is typically complicated, large, and slow. Here we present Agents.jl, a Julia-based software that provides an ABM analysis platform with minimal code complexity. We compare our software with some of the most popular ABM software in other programming languages. We find that Agents.jl is not only the most performant but also the least complicated software, providing the same (and sometimes more) features as the competitors with less input required from the user. Agents.jl also integrates excellently with the entire Julia ecosystem, including interactive applications, differential equations, parameter optimization, and so on. This removes any “extensions library” requirement from Agents.jl, which is paramount in many other tools.

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Datseris G., Vahdati A. R., DuBois T. C. Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity // Simulation. 2022. Vol. 100. No. 10. p. 003754972110688.
GOST all authors (up to 50) Copy
Datseris G., Vahdati A. R., DuBois T. C. Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity // Simulation. 2022. Vol. 100. No. 10. p. 003754972110688.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1177/00375497211068820
UR - https://journals.sagepub.com/doi/10.1177/00375497211068820
TI - Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity
T2 - Simulation
AU - Datseris, George
AU - Vahdati, Ali R.
AU - DuBois, Timothy C.
PY - 2022
DA - 2022/01/05
PB - SAGE
SP - 003754972110688
IS - 10
VL - 100
SN - 0037-5497
SN - 1741-3133
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2022_Datseris,
author = {George Datseris and Ali R. Vahdati and Timothy C. DuBois},
title = {Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity},
journal = {Simulation},
year = {2022},
volume = {100},
publisher = {SAGE},
month = {jan},
url = {https://journals.sagepub.com/doi/10.1177/00375497211068820},
number = {10},
pages = {003754972110688},
doi = {10.1177/00375497211068820}
}
MLA
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Datseris, George, et al. “Agents.jl: a performant and feature-full agent-based modeling software of minimal code complexity.” Simulation, vol. 100, no. 10, Jan. 2022, p. 003754972110688. https://journals.sagepub.com/doi/10.1177/00375497211068820.
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