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Adaptive Learning and Emergent Coordination in Minority Games


  • Giulio Bottazzi
  • Giovanna Devetag
  • Giovanni Dosi


The work studies the properties of a coordination game in which agents repeatedly compete to be in the population minority. The game reflects some essential features of those economic situations in which positive rewards are assigned to individuals who behave in opposition to the modal behavior in a population. Here we model a group of heterogeneous agents who adaptively learn and we investigate the transient and long-run aggregate properties of the system in terms of both allocative and informational efficiency. Our results show that, first, the system long-run properties strongly depend on the behavioral learning rules adopted, and, second, adding noise at the individual decision level and hence increasing heterogeneity in the population substantially improve aggregate welfare, although at the expense of a longer adjustment phase. In fact, the system achieves in that way a higher level of efficiency compared to that attainable by perfectly rational and completely informed agents.

Suggested Citation

  • Giulio Bottazzi & Giovanna Devetag & Giovanni Dosi, 1999. "Adaptive Learning and Emergent Coordination in Minority Games," LEM Papers Series 1999/24, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  • Handle: RePEc:ssa:lemwps:1999/24

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    1. Andrea Bonaccorsi & Paola Giuri, 1999. "Non shakeout patterns of industry evolution. The case of turboprop engine industry," LEM Papers Series 1999/10, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    2. Kirk Monteverde & David J. Teece, 1982. "Supplier Switching Costs and Vertical Integration in the Automobile Industry," Bell Journal of Economics, The RAND Corporation, vol. 13(1), pages 206-213, Spring.
    3. Bresnahan, Timothy F & Greenstein, Shane, 1999. "Technological Competition and the Structure of the Computer Industry," Journal of Industrial Economics, Wiley Blackwell, vol. 47(1), pages 1-40, March.
    4. Riordan, Michael H, 1998. "Anticompetitive Vertical Integration by a Dominant Firm," American Economic Review, American Economic Association, vol. 88(5), pages 1232-1248, December.
    5. Lustgarten, Steven H, 1975. "The Impact of Buyer Concentration in Manufacturing Industries," The Review of Economics and Statistics, MIT Press, vol. 57(2), pages 125-132, May.
    6. Orsenigo, L. & Pammolli, F. & Riccaboni, Massimo, 2001. "Technological change and network dynamics: Lessons from the pharmaceutical industry," Research Policy, Elsevier, vol. 30(3), pages 485-508, March.
    7. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    8. Andrea Bonaccorsi & Paola Giuri, 1999. "Increasing returns and network structure in the evolutionary dynamics of industries," LEM Papers Series 1999/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Bengt Holmstrom & John Roberts, 1998. "The Boundaries of the Firm Revisited," Journal of Economic Perspectives, American Economic Association, vol. 12(4), pages 73-94, Fall.
    10. Klepper, Steven, 1997. "Industry Life Cycles," Industrial and Corporate Change, Oxford University Press, vol. 6(1), pages 145-181.
    11. Klein, Benjamin & Crawford, Robert G & Alchian, Armen A, 1978. "Vertical Integration, Appropriable Rents, and the Competitive Contracting Process," Journal of Law and Economics, University of Chicago Press, vol. 21(2), pages 297-326, October.
    12. Hart, O. & Tirole, J., 1990. "Vertical Integration And Market Foreclosure," Working papers 548, Massachusetts Institute of Technology (MIT), Department of Economics.
    13. Luigi Orsenigo & Fabio Pammolli & Massimo Riccaboni & Andrea Bonaccorsi & Giuseppe Turchetti, 1997. "The Evolution of Knowledge and the Dynamics of an Industry Network," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 1(2), pages 147-175, June.
    14. Joseph Farrell & Hunter K. Monroe & Garth Saloner, 1998. "The Vertical Organization of Industry: Systems Competition versus Component Competition," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 7(2), pages 143-182, June.
    15. von Ungern-Sternberg, Thomas, 1996. "Countervailing power revisited," International Journal of Industrial Organization, Elsevier, vol. 14(4), pages 507-519, June.
    16. Andrea Bonaccorsi & Paola Giuri, 2000. "Industry Life Cycle and the Evolution of an Industry Network," LEM Papers Series 2000/04, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
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    Cited by:

    1. Kets, W., 2007. "The Minority Game : An Economics Perspective," Discussion Paper 2007-53, Tilburg University, Center for Economic Research.
    2. Giorgio Fagiolo & Marco Valente, 2005. "Minority Games, Local Interactions, and Endogenous Networks," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 41-57, February.
    3. 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.
    4. Földy, Csaba & Somogyvári, Zoltán & Érdi, Péter, 2003. "Hierarchically organized minority games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 323(C), pages 735-742.

    More about this item


    minority game; speculation; adaptive learning; market efficiency; emergent properties;

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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