Agent-Based Modelling: Tools for Linking NetLogo and r

Jan C. Thiele (), Winfried Kurth () and Volker Grimm ()
Additional contact information
Jan C. Thiele: https://www.uni-goettingen.de/en/72779.html
Winfried Kurth: http://www.uni-goettingen.de/en/72781.html
Volker Grimm: https://www.ufz.de/index.php?de=36522

Journal of Artificial Societies and Social Simulation, 2012, vol. 15, issue 3, 8

Abstract: A seamless integration of software platforms for implementing agent-based models and for analysing their output would facilitate comprehensive model analyses and thereby make agent-based modelling more useful. Here we report on recently developed tools for linking two widely used software platforms: NetLogo for implementing agent-based models, and R for the statistical analysis and design of experiments. Embedding R into NetLogo allows the use of advanced statistical analyses, specific statistical distributions, and advanced tools for visualization from within NetLogo programs. Embedding NetLogo into R makes it possible to design simulation experiments and all settings for analysing model output from the outset, using R, and then embed NetLogo programs in this virtual laboratory. Our linking tools have the potential to significantly advance research based on agent-based modelling.

Keywords: Agent-Based Modelling; Design of Experiments; R; NetLogo; Model Analysis; Modelling Software (search for similar items in EconPapers)
Date: 2012-06-30
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.jasss.org/15/3/8/8.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2012-39-2

Access Statistics for this article

More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Francesco Renzini ().