IDEAS home Printed from
   My bibliography  Save this article

What economic agents do: How cognition and interaction lead to emergence and complexity


  • Robert Axtell


Kohn (The Cato Journal, 24(3):303–339, 2004) has argued that the neoclassical conception of economics—what he terms the “value paradigm”—has experienced diminishing marginal returns for some time. He suggests a new perspective is emerging—one that gives more import to economic processes and less to end states, one that bases behavior less on axioms and more on laboratory experiments. He calls this the “exchange paradigm”. He further asserts that it is the mathematization of economics that is partially at fault for leading the profession down a methodological path that has become something of a dead end. Here I suggest that the nascent research program Kohn has rightly spotted is better understood as distinct from its precursors because it is intrinsically dynamic, permits agent actions out of equilibrium, and treats such actions as occurring within networks. Analyzing economic processes having these characteristics is mathematically very difficult and I concur with Kohn’s appeal to computational approaches. However, I claim it is so-called multi-agent systems and agent-based models that are the way forward within the “exchange paradigm,” and not the cellular automata (Wolfram, A new kind of science, 2002) that Kohn seems to promote. Agent systems are generalizations of cellular automata and support the natural abstraction of individual economic agents as software agents. Copyright Springer Science+Business Media, LLC 2007

Suggested Citation

  • Robert Axtell, 2007. "What economic agents do: How cognition and interaction lead to emergence and complexity," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 20(2), pages 105-122, September.
  • Handle: RePEc:kap:revaec:v:20:y:2007:i:2:p:105-122
    DOI: 10.1007/s11138-007-0021-5

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    File URL:
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Blume Lawrence E., 1995. "The Statistical Mechanics of Best-Response Strategy Revision," Games and Economic Behavior, Elsevier, vol. 11(2), pages 111-145, November.
    2. LeBaron, Blake, 2001. "Evolution And Time Horizons In An Agent-Based Stock Market," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 225-254, April.
    3. Meir Kohn, 2004. "Value and Exchange," Cato Journal, Cato Journal, Cato Institute, vol. 24(3), pages 303-339, Fall.
    4. Foley Duncan K., 1994. "A Statistical Equilibrium Theory of Markets," Journal of Economic Theory, Elsevier, vol. 62(2), pages 321-345, April.
    5. Leigh TESFATSION, 1995. "How Economists Can Get Alife," Economic Report 37, Iowa State University Department of Economics.
    6. Blume Lawrence E., 1993. "The Statistical Mechanics of Strategic Interaction," Games and Economic Behavior, Elsevier, vol. 5(3), pages 387-424, July.
    7. Ralph Bradburd & Stephen Sheppard & Joseph Bergeron & Eric Engler, 2006. "The Impact Of Rent Controls In Non‐Walrasian Markets: An Agent‐Based Modeling Approach," Journal of Regional Science, Wiley Blackwell, vol. 46(3), pages 455-491, August.
    8. Ashlock, Dan & Smucker, Mark & Stanley, E. Ann & Tesfatsion, Leigh, 1994. "Preferential Partner Selection in an Evolutionary Study of Prisoner's Dilemma," ISU General Staff Papers 199409010700001033, Iowa State University, Department of Economics.
    9. Tesfatsion, Leigh, 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," ISU General Staff Papers 200201010800001251, Iowa State University, Department of Economics.
    10. Howitt, Peter & Clower, Robert, 2000. "The emergence of economic organization," Journal of Economic Behavior & Organization, Elsevier, vol. 41(1), pages 55-84, January.
    11. Colin F. Camerer, 1997. "Progress in Behavioral Game Theory," Journal of Economic Perspectives, American Economic Association, vol. 11(4), pages 167-188, Fall.
    12. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    13. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, Oxford University Press, vol. 108(1), pages 137-156.
    14. repec:cto:journl:v:24:y:2004:i:3:p: is not listed on IDEAS
    15. Robert Axtell, 2005. "The Complexity of Exchange," Economic Journal, Royal Economic Society, vol. 115(504), pages 193-210, June.
    16. Vincent Darley & Alexander V Outkin, 2007. "Learning, Evolution and Tick Size Effects," World Scientific Book Chapters, in: A Nasdaq Market Simulation Insights on a Major Market from the Science of Complex Adaptive Systems, chapter 5, pages 81-87, World Scientific Publishing Co. Pte. Ltd..
    17. Herbert A. Simon, 1978. "On How to Decide What to Do," Bell Journal of Economics, The RAND Corporation, vol. 9(2), pages 494-507, Autumn.
    18. Hahn, Robert W, 1989. "Economic Prescriptions for Environmental Problems: How the Patient Followed the Doctor's Orders," Journal of Economic Perspectives, American Economic Association, vol. 3(2), pages 95-114, Spring.
    19. 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.
    Full references (including those not matched with items on IDEAS)

    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. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    2. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354,
    3. Tesfatsion, Leigh, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," ISU General Staff Papers 199807010700001043, Iowa State University, Department of Economics.
    4. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140,
    5. Santiago J. Gangotena, 2017. "Dynamic coordinating non-equilibrium," The Review of Austrian Economics, Springer;Society for the Development of Austrian Economics, vol. 30(1), pages 51-82, March.
    6. Roman Šperka & Irena Szarowská, 2015. "Impact of a Financial Transaction Tax on a Financial Market," Working Papers 0013, Silesian University, School of Business Administration.
    7. Luca Riccetti & Alberto Russo & Mauro Gallegati, 2015. "An agent based decentralized matching macroeconomic model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 10(2), pages 305-332, October.
    8. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    9. 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.
    10. Sornette, Didier & Zhou, Wei-Xing, 2006. "Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 704-726.
    11. Leigh TESFATSION, 1995. "How Economists Can Get Alife," Economic Report 37, Iowa State University Department of Economics.
    12. Torsten Trimborn & Philipp Otte & Simon Cramer & Maximilian Beikirch & Emma Pabich & Martin Frank, 2020. "SABCEMM: A Simulator for Agent-Based Computational Economic Market Models," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 707-744, February.
    13. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    14. Georges, Christophre, 2008. "Staggered updating in an artificial financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2809-2825, September.
    15. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    16. Tesfatsion, Leigh, 1998. "Gale-Shapley Matching in an Evolutionary Trade Network Game," ISU General Staff Papers 199804010800001041, Iowa State University, Department of Economics.
    17. Raquel Ramos & Federico Bassi & Dany Lang, 2020. "Bet against the trend and cash in profits," CEPN Working Papers halshs-02956879, HAL.
    18. M.G. Zimmermann, V. M. Eguiluz, 2001. "Evolution of Cooperative Networks and the Emergence of Leadership," Computing in Economics and Finance 2001 171, Society for Computational Economics.
    19. T. Kaizoji & M. Leiss & A. Saichev & D. Sornette, 2011. "Super-exponential endogenous bubbles in an equilibrium model of rational and noise traders," Papers 1109.4726,, revised Mar 2014.
    20. Simon Cramer & Torsten Trimborn, 2019. "Stylized Facts and Agent-Based Modeling," Papers 1912.02684,

    More about this item


    Agent-based modeling; Heterogeneous agents; Self-organizing systems; Emergence; Complexity; B4; D5; D8;
    All these keywords.

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty


    Access and download statistics


    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:kap:revaec:v:20:y:2007:i:2:p:105-122. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.