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Minority Games, Local Interactions, and Endogenous Networks

Author

Listed:
  • Valente M.
  • Fagiolo G.

Abstract

In this paper we study a local version of the Minority Game where agents are placed on the nodes of a directed graph. Agents care about beingin the minority of the group of agents they are currently linked to and employ myopic best-reply rules to choose their next-period state. We show that, in this benchmark case, the smaller the size of local networks, the larger long-run population-average payoffs. We then explore the collective behavior of the system when agents can: (i) assign weights to each link they hold and modify them over time in response to payoff signals; (ii) delete badly-performing links (i.e. opponents) and replace them with randomly chosen ones. Simulations suggest that, when agents are allowed to weight links but cannot delete/replace them, the system self-organizes into networked clusters which attain very high payoff values. These clustered configurations are not stable and can be easily disrupted, generating huge subsequent payoff drops. If however agents can (and are sufficiently willing to) discard badly performing connections, the system quickly converges to stable states where all agents get the highest payoff, independently of the size of the networks initially in place

Suggested Citation

  • Valente M. & Fagiolo G., 2004. "Minority Games, Local Interactions, and Endogenous Networks," Computing in Economics and Finance 2004 110, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:110
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    References listed on IDEAS

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    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. Giorgio Fagiolo & Luigi Marengo & Marco Valente, 2004. "Endogenous Networks In Random Population Games," Mathematical Population Studies, Taylor & Francis Journals, pages 121-147.
    3. Weisbuch, Gerard & Kirman, Alan & Herreiner, Dorothea, 2000. "Market Organisation and Trading Relationships," Economic Journal, Royal Economic Society, vol. 110(463), pages 411-436, April.
    4. 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.
    5. Burgos, E. & Ceva, Horacio & Perazzo, R.P.J., 2004. "The evolutionary minority game with local coordination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 337(3), pages 635-644.
    6. 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.
    7. Fagiolo, Giorgio, 2005. "Endogenous neighborhood formation in a local coordination model with negative network externalities," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 297-319, January.
    8. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-411, May.
    9. Challet, Damien & Marsili, Matteo & Zhang, Yi-Cheng, 2000. "Modeling market mechanism with minority game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 276(1), pages 284-315.
    10. Challet, D. & Zhang, Y.-C., 1997. "Emergence of cooperation and organization in an evolutionary game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 407-418.
    11. Challet, Damien & Zhang, Yi-Cheng, 1998. "On the minority game: Analytical and numerical studies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 256(3), pages 514-532.
    12. Slanina, František, 2000. "Social organization in the Minority Game model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 286(1), pages 367-376.
    13. 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.
    14. Kalinowski, Thomas & Schulz, Hans-Jörg & Briese, Michael, 2000. "Cooperation in the Minority Game with local information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 277(3), pages 502-508.
    15. Alan Kirman, 1997. "The economy as an evolving network," Journal of Evolutionary Economics, Springer, vol. 7(4), pages 339-353.
    16. Moelbert, S. & De Los Rios, P., 2002. "The local minority game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 217-225.
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    Cited by:

    1. Zakaria Babutsidze, 2012. "Consumer Learning through Interaction: Effects on Aggregate Outcomes," Chapters,in: Evolution, Organization and Economic Behavior, chapter 4 Edward Elgar Publishing.
    2. Zhang, Wei & Sun, Yuxin & Feng, Xu & Xiong, Xiong, 2015. "Evolutionary Minority Game with searching behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 694-706.

    More about this item

    Keywords

    Minority Games; Local Interactions; Non-Directed Graphs; Endogenous Networks; Adaptive Systems.;

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General

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