IDEAS home Printed from https://ideas.repec.org/p/wop/safiwp/00-07-039.html
   My bibliography  Save this paper

Effect of Interaction Topology and Activation Regime in Several Multi-Agent Systems

Author

Listed:
  • Robert L. Axtell

Abstract

The effects of distinct agent interaction and activation structures are compared and contrasted in several multi-agent models of social phenomena. Random graphs and lattices represent two limiting kinds of agent interaction networks studied, with so-called 'small-world' networks being an intermediate form between these two extremes. A model of retirement behavior is studied with each network type, resulting in important differences in key model outputs. Then, in the context of a model of firm formation, in which multi-agent structures (firms) are emergent, it is demonstrated that the medium of interaction -- whether through individual agents or through firms -- affects the qualitative character of the results. Finally, alternative agent activation 'schedules' are studied. In particular, two activation modes are compared: (1) all agents being active exactly once each period, and (2) each agent having a random number of activations in every period with mean 1. In many circumstances these two regimes produce indistinguishable results at the aggregate level, but in certain cases the differences between them are significant.

Suggested Citation

  • Robert L. Axtell, 2000. "Effect of Interaction Topology and Activation Regime in Several Multi-Agent Systems," Working Papers 00-07-039, Santa Fe Institute.
    • Handle: RePEc:wop:safiwp:00-07-039
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    References listed on IDEAS

    as
    1. Ellison, Glenn, 1993. "Learning, Local Interaction, and Coordination," Econometrica, Econometric Society, vol. 61(5), pages 1047-1071, September.
    2. Page, Scott E, 1997. "On Incentives and Updating in Agent Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 10(1), pages 67-87, February.
    3. Robert Axtell & Robert Axelrod & Joshua M. Epstein & Michael D. Cohen, 1995. "Aligning Simulation Models: A Case Study and Results," Working Papers 95-07-065, Santa Fe Institute.
    4. Young, H.P., 1999. "Diffusion in Social Networks," Papers 2, Brookings Institution - Working Papers.
    5. 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, December.
    6. Robert Axtell, 1999. "The Emergence of Firms in a Population of Agents," Working Papers 99-03-019, Santa Fe Institute.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yves Saillard, 2004. "L'analyse économique des normes : représentation et traitement des interactions dans les modèles de simulation," Post-Print halshs-00104866, HAL.
    2. Jacques Laye & Charis Lina & Herve Tanguy, 2006. "E-consumers' search and emerging structure of B-to-C coalitions," Computing in Economics and Finance 2006 374, Society for Computational Economics.
    3. Levy, David M. & Makowsky, Michael D., 2010. "Price dispersion and increasing returns to scale," Journal of Economic Behavior & Organization, Elsevier, vol. 73(3), pages 406-417, March.
    4. van der Hoog, Sander, 2008. "On the disequilibrium dynamics of sequential monetary economies," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 525-552, December.
    5. Paul L. Borrill & Leigh Tesfatsion, 2011. "Agent-based Modeling: The Right Mathematics for the Social Sciences?," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 11, Edward Elgar Publishing.
    6. Denis Phan & Stephane Pajot & Jean-Pierre Nadal, 2003. "The Monopolist's Market with Discrete Choices and Network Externality Revisited: Small-Worlds, Phase Transition and Avalanches in an ACE Framework," Computing in Economics and Finance 2003 150, Society for Computational Economics.
    7. Merenda, João V.B.S. & Bruno, Odemir M., 2023. "Using deterministic self-avoiding walks as a small-world metric on Watts–Strogatz networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 621(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joshua M. Epstein, 2007. "Agent-Based Computational Models and Generative Social Science," Introductory Chapters, in: Generative Social Science Studies in Agent-Based Computational Modeling, Princeton University Press.
    2. Zakaria Babutsidze, 2012. "Consumer Learning through Interaction: Effects on Aggregate Outcomes," Chapters, in: Guido Buenstorf (ed.), Evolution, Organization and Economic Behavior, chapter 4, Edward Elgar Publishing.
    3. Uri Wilensky & William Rand, 2007. "Making Models Match: Replicating an Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-2.
    4. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    5. Giorgio Fagiolo, 2001. "Coordination, Local Interactions and Endogenous Neighborhood Formation," LEM Papers Series 2001/15, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    6. Bill Gibson, 2008. "Keynesian And Neoclassical Closures In An Agent-Based Context," UMASS Amherst Economics Working Papers 2008-03, University of Massachusetts Amherst, Department of Economics.
    7. Edgardo Bucciarelli & Marcello Silvestri, 2013. "Hyman P. Minsky's unorthodox approach: recent advances in simulation techniques to develop his theoretical assumptions," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 36(2), pages 299-324.
    8. Cassar, Alessandra, 2007. "Coordination and cooperation in local, random and small world networks: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 58(2), pages 209-230, February.
    9. Tesfatsion, Leigh, 1998. "Gale-Shapley Matching in an Evolutionary Trade Network Game," ISU General Staff Papers 199804010800001041, Iowa State University, Department of Economics.
    10. Frans Prenkert, 2012. "Business Network Simulation: Combining Research Cases and Agent-Based Models in a Robust Methodology," International Journal of Business Administration, International Journal of Business Administration, Sciedu Press, vol. 3(6), pages 82-92, November.
    11. Giorgio Fagiolo & Luigi Marengo & Marco Valente, 2004. "Endogenous Networks In Random Population Games," Mathematical Population Studies, Taylor & Francis Journals, vol. 11(2), pages 121-147.
    12. Zhang, Junfu, 2004. "Residential segregation in an all-integrationist world," Journal of Economic Behavior & Organization, Elsevier, vol. 54(4), pages 533-550, August.
    13. Brian Heath & Raymond Hill & Frank Ciarallo, 2009. "A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-9.
    14. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    15. Bill Gibson, 2007. "A Multi-Agent Systems Approach to Microeconomic Foundations of Macro," UMASS Amherst Economics Working Papers 2007-10, University of Massachusetts Amherst, Department of Economics.
    16. A. Pyka & G. Fagiolo, 2007. "Agent-based Modelling: A Methodology for Neo-Schumpetarian Economics," Chapters, in: Horst Hanusch & Andreas Pyka (ed.), Elgar Companion to Neo-Schumpeterian Economics, chapter 29, Edward Elgar Publishing.
    17. Sebastiano A. Delre & Wander Jager & Marco A. Janssen, 2007. "Diffusion dynamics in small-world networks with heterogeneous consumers," Computational and Mathematical Organization Theory, Springer, vol. 13(2), pages 185-202, June.
    18. Davis, Jon S. & Pesch, Heather L., 2013. "Fraud dynamics and controls in organizations," Accounting, Organizations and Society, Elsevier, vol. 38(6), pages 469-483.
    19. Ge, Jiaqi, 2014. "Stepping into new territory: Three essays on agent-based computational economics and environmental economics," ISU General Staff Papers 201401010800004899, Iowa State University, Department of Economics.
    20. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wop:safiwp:00-07-039. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thomas Krichel (email available below). General contact details of provider: https://edirc.repec.org/data/epstfus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.