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R Marries NetLogo: Introduction to the RNetLogo Package

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  • Thiele, Jan C

Abstract

The RNetLogo package delivers an interface to embed the agent-based modeling platform NetLogo into the R environment with headless (no graphical user interface) or interactive GUI mode. It provides functions to load models, execute commands, push values, and to get values from NetLogo reporters. Such a seamless integration of a widely used agent-based modeling platform with a well-known statistical computing and graphics environment opens up various possibilities. For example, it enables the modeler to design simulation experiments, store simulation results, and analyze simulation output in a more systematic way. It can therefore help close the gaps in agent-based modeling regarding standards of description and analysis. After a short overview of the agent-based modeling approach and the software used here, the paper delivers a step-by-step introduction to the usage of the RNetLogo package by examples.

Suggested Citation

  • Thiele, Jan C, 2014. "R Marries NetLogo: Introduction to the RNetLogo Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i02).
  • Handle: RePEc:jss:jstsof:v:058:i02
    DOI: http://hdl.handle.net/10.18637/jss.v058.i02
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    1. LeBaron, Blake, 2000. "Agent-based computational finance: Suggested readings and early research," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 679-702, June.
    2. Arifovic, Jasmina, 1994. "Genetic algorithm learning and the cobweb model," Journal of Economic Dynamics and Control, Elsevier, vol. 18(1), pages 3-28, January.
    3. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    4. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    5. Regine Pei Tze Oh & Susan M. Sanchez & Thomas W. Lucas & Hong Wan & Mark E. Nissen, 2009. "Efficient experimental design tools for exploring large simulation models," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 237-257, September.
    6. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    7. Flaminio Squazzoni, 2010. "The impact of agent-based models in the social sciences after 15 years of incursions," History of Economic Ideas, Fabrizio Serra Editore, Pisa - Roma, vol. 18(2), pages 197-234.
    8. Bowman, Adrian & Crawford, Ewan & Alexander, Gavin & Bowman, Richard W, 2007. "rpanel: Simple Interactive Controls for R Functions Using the tcltk Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i09).
    9. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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    7. Fanny A. Kluge & Tobias C. Vogt, 2020. "Intergenerational transfers within the family and the role for old age survival," MPIDR Working Papers WP-2020-021, Max Planck Institute for Demographic Research, Rostock, Germany.

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