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Evolving Game Strategies in a Dynamic Cournot Oligopoly Setting

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EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 674))

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Abstract

A Cournot oligopoly is used as a benchmark for Nash equilibria tracking and detection in a dynamic setting. Several dynamics that induce different trajectories for the equilibria are considered: random, linear, cosine, and spiral. A new Extremal Optimization based method is tested on the proposed dynamic setting.

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Acknowledgments

The authors would like to acknowledge the support received from the OPEN-RES 212/2012 grant (www.uefiscdi.gov.ro).

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Authors and Affiliations

  1. Centre for the Study of Complexity, Babeş-Bolyai University, Cluj Napoca, Romania

    Mihai Alexandru Suciu, Rodica-Ioana Lung, Noémi Gaskó, Tudor-Dan Mihoc & Dan Dumitrescu

Authors
  1. Mihai Alexandru Suciu
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  2. Rodica-Ioana Lung
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  3. Noémi Gaskó
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  4. Tudor-Dan Mihoc
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  5. Dan Dumitrescu
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Corresponding author

Correspondence to Mihai Alexandru Suciu .

Editor information

Editors and Affiliations

  1. Computer Science and Communications Research Unit, University of Luxembourg E009 (CSC) Kirchberg Campus, Luxembourg, Luxembourg

    Alexandru-Adrian Tantar

  2. Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg, Luxembourg

    Emilia Tantar

  3. Leiden Institute of Advanced Computer Science, Leiden University, Leiden, The Netherlands

    Michael Emmerich

  4. Bâtiment Leyteire, URF Sciences et Modelisation, Université Bordeaux, Bordeaux, France

    Pierrick Legrand

  5. Faculty of Computer Science, Alexandru Ioan Cuza University of Iași, Iași, Romania

    Lenuta Alboaie

  6. Faculty of Computer Science, Alexandru Ioan Cuza University, Iasi, Romania

    Henri Luchian

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Suciu, M.A., Lung, RI., Gaskó, N., Mihoc, TD., Dumitrescu, D. (2018). Evolving Game Strategies in a Dynamic Cournot Oligopoly Setting. In: Tantar, AA., Tantar, E., Emmerich, M., Legrand, P., Alboaie, L., Luchian, H. (eds) EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation VI. Advances in Intelligent Systems and Computing, vol 674. Springer, Cham. https://doi.org/10.1007/978-3-319-69710-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-69710-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69708-6

  • Online ISBN: 978-3-319-69710-9

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