IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-03916500.html
   My bibliography  Save this paper

From Agent-Based Computational Economics towards Cognitive Economics

Author

Listed:
  • Denis Phan

    (GEMASS - Groupe d'Etude des Méthodes de l'Analyse Sociologique de la Sorbonne - FMSH - Fondation Maison des sciences de l'homme - SU - Sorbonne Université - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper provides a short introduction to Agent-based Computational Economics (ACE), in order to underline the interest of such an approach in cognitive economics. Section 2 provides a brief bird's eye view of ACE. In section 3, some interesting features of the Santa-Fe Approach to complexity are then introduced by taking simple examples using the Moduleco computational laboratory. Section 4 provides a short introduction to the object-oriented architecture of the Moduleco's framework. Section 5 underlines the interest of ACE for modelling and exploring dynamic features of markets viewed as cognitive and complex social interactive systems. Simple examples of simulations based on two cognitive economics models are briefly discussed. The first one, deals with the so-called exploration-exploitation compromise, while the second deal with social influence and dynamics over social networks.

Suggested Citation

  • Denis Phan, 2004. "From Agent-Based Computational Economics towards Cognitive Economics," Post-Print halshs-03916500, HAL.
  • Handle: RePEc:hal:journl:halshs-03916500
    DOI: 10.1007/978-3-540-24708-1_22
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03916500
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-03916500/document
    Download Restriction: no

    File URL: https://libkey.io/10.1007/978-3-540-24708-1_22?utm_source=ideas
    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
    ---><---

    References listed on IDEAS

    as
    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. R. Baron & Jacques Durieu & Hans Haller & Philippe Solal, 2004. "Stochastic Evolutionary Game Theory," Post-Print halshs-03216673, HAL.
    3. Jean Pierre Nadal & Denis Phan & Mirta B. Gordan & Jean Vannimenus, 2003. "Monopoly Market with Externality: an Analysis with Statistical Physics and ACE," Computational Economics 0312002, University Library of Munich, Germany.
    4. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    5. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.
    6. Rothschild, Michael, 1974. "A two-armed bandit theory of market pricing," Journal of Economic Theory, Elsevier, vol. 9(2), pages 185-202, October.
    7. Miles Parker, 2001. "What is Ascape and Why Should You Care?," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(1), pages 1-5.
    8. Lane, David A, 1993. "Artificial Worlds and Economics, Part I," Journal of Evolutionary Economics, Springer, vol. 3(2), pages 89-107, May.
    9. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    10. Vriend, Nicolaas J, 1995. "Self-Organization of Markets: An Example of a Computational Approach," Computational Economics, Springer;Society for Computational Economics, vol. 8(3), pages 205-231, August.
    11. Orlean, Andre, 1995. "Bayesian interactions and collective dynamics of opinion: Herd behavior and mimetic contagion," Journal of Economic Behavior & Organization, Elsevier, vol. 28(2), pages 257-274, October.
    12. Alan Kirman, 1993. "Ants, Rationality, and Recruitment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(1), pages 137-156.
    13. Kirman, Alan P., 1983. "Communication in markets : A suggested approach," Economics Letters, Elsevier, vol. 12(2), pages 101-108.
    14. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
    15. 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.
    16. Lane, David A, 1993. "Artificial Worlds and Economics, Part II," Journal of Evolutionary Economics, Springer, vol. 3(3), pages 177-197, August.
    17. B. LeBaron, 2001. "A builder's guide to agent-based financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 254-261.
    18. Alan Kirman, 1997. "The economy as an evolving network," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 339-353.
    19. Lesourne, Jacques, 1992. "The Economics of Order and Disorder: The Market as Organizer and Creator," OUP Catalogue, Oxford University Press, number 9780198287391.
    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. 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.
    2. 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.
    3. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    4. Leigh Tesfatsion, 1998. "Teaching Agent-Based Computational Economics to Graduate Students," Computational Economics 9809001, University Library of Munich, Germany, revised 16 Nov 1998.
    5. repec:dgr:rugsom:99b41 is not listed on IDEAS
    6. 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.
    7. Tomas Klos, 1999. "Governance and Matching," Computing in Economics and Finance 1999 341, Society for Computational Economics.
    8. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    9. Klos, Tomas B. & Nooteboom, Bart, 2001. "Agent-based computational transaction cost economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 503-526, March.
    10. Youwei Li & Xue-Zhong He, 2005. "Long Memory, Heterogeneity, and Trend Chasing," Computing in Economics and Finance 2005 113, Society for Computational Economics.
    11. Alexander Gorobets & Bart Nooteboom, 2006. "Adaptive Build-up and Breakdown of Trust: An Agent Based Computational Approach," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 10(3), pages 277-306, September.
    12. Hossein Sabzian & Mohammad Ali Shafia & Ali Maleki & Seyeed Mostapha Seyeed Hashemi & Ali Baghaei & Hossein Gharib, 2019. "Theories and Practice of Agent based Modeling: Some practical Implications for Economic Planners," Papers 1901.08932, arXiv.org.
    13. 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.
    14. Andreas Ortmann & Sergey Slobodyan & Samuel S. Nordberg, 2003. "(The Evolution of) Post-Secondary Education: A Computational Model and Experiments," CERGE-EI Working Papers wp208, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    15. Hossein Sabzian & Alireza Aliahmadi & Adel Azar & Madjid Mirzaee, 2018. "Economic inequality and Islamic Charity: An exploratory agent-based modeling approach," Papers 1804.09284, arXiv.org.
    16. Delli Gatti,Domenico & Fagiolo,Giorgio & Gallegati,Mauro & Richiardi,Matteo & Russo,Alberto (ed.), 2018. "Agent-Based Models in Economics," Cambridge Books, Cambridge University Press, number 9781108400046, October.
    17. Garavaglia, Christian, 2010. "Modelling industrial dynamics with "History-friendly" simulations," Structural Change and Economic Dynamics, Elsevier, vol. 21(4), pages 258-275, November.
    18. Denis Becker & Alexei Gaivoronski, 2014. "Stochastic optimization on social networks with application to service pricing," Computational Management Science, Springer, vol. 11(4), pages 531-562, October.
    19. 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.
    20. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    21. Alan Kirman, 2002. "Reflections on interaction and markets," Quantitative Finance, Taylor & Francis Journals, vol. 2(5), pages 322-326.

    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:hal:journl:halshs-03916500. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.