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Systematic Approach Ton-Person Social Dilemma Games: Classification And Analysis

Author

Listed:
  • UGO MERLONE

    (Psychology Department, University of Torino, via Verdi 10 10124 Torino, Italy)

  • DAREN R. SANDBANK

    (Systems and Industrial Engineering Department, University of Arizona, Tucson, Arizona 85721-0020, USA)

  • FERENC SZIDAROVSZKY

    (Department of Applied Mathematics, University of Pécs, Pécs, Hungary, H-7624, Hungary)

Abstract

This paper presents a new systematic review ofN-person social dilemma games using a new approach based on dynamic properties of the corresponding system. TraditionallyN-person social dilemma games are classified by relative orders of magnitude of payoff parameters. Without border-line cases 24 are identified. The new approach introduced in this paper categorizes the social dilemma games in cases with different number and asymptotic properties of the equilibria. In these cases the solution structure or the trajectory of the percentage of cooperators is readily apparent. These cases also provide the modeler with additional information concerning the impacts of the model parameters on the game outcomes. The example of a simple cartel illustrates this methodology.

Suggested Citation

  • Ugo Merlone & Daren R. Sandbank & Ferenc Szidarovszky, 2012. "Systematic Approach Ton-Person Social Dilemma Games: Classification And Analysis," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 1-25.
    • Handle: RePEc:wsi:igtrxx:v:14:y:2012:i:03:n:s0219198912500156
    DOI: 10.1142/S0219198912500156
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    References listed on IDEAS

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    1. Dal Forno, Arianna & Merlone, Ugo, 2013. "Border-collision bifurcations in a model of Braess paradox," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 87(C), pages 1-18.
    2. Ugo Merlone & Daren Sandbank & Ferenc Szidarovszky, 2013. "Equilibria analysis in social dilemma games with Skinnerian agents," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 12(2), pages 219-233, November.
    3. 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.
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    Cited by:

    1. Marcel Ausloos & Herbert Dawid & Ugo Merlone, 2015. "Spatial Interactions in Agent-Based Modeling," Dynamic Modeling and Econometrics in Economics and Finance, in: Pasquale Commendatore & Saime Kayam & Ingrid Kubin (ed.), Complexity and Geographical Economics, edition 127, pages 353-377, Springer.
    2. Tadeusz Płatkowski, 2017. "On Derivation and Evolutionary Classification of Social Dilemma Games," Dynamic Games and Applications, Springer, vol. 7(1), pages 67-75, March.

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    More about this item

    Keywords

    Social dilemmas; agent-based simulation; N-person games; Pavlovian agents; equilibrium; 91A06; 91A26; 91E10;
    All these keywords.

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C0 - Mathematical and Quantitative Methods - - General
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • D5 - Microeconomics - - General Equilibrium and Disequilibrium
    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics

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