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Nash Extremal Optimization and Large Cournot Games

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Nature Inspired Cooperative Strategies for Optimization (NICSO 2011)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 387))

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Abstract

Equilibria detection in large games represents an important challenge in computational game theory. A solution based on generative relations defined on the strategy set and the standard Extremal Optimization algorithm is proposed. The Cournot oligopoly model involving up to 1000 players is used to test the proposed methods. Results are compared with those obtained by a Crowding Differential Evolution algorithm.

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Author information

Authors and Affiliations

  1. Babes-Bolyai University, Romania

    Rodica Ioana Lung, Tudor Dan Mihoc & D. Dumitrescu

Authors
  1. Rodica Ioana Lung
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  2. Tudor Dan Mihoc
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  3. D. Dumitrescu
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Editors and Affiliations

  1. Dept. of Computer Science and A.I.E.T.S. Ingenieria Informatica y de Telecomunicación, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n,, 18071, Granada, Spain

    David Alejandro Pelta

  2. School of Computer Science, University of Nottingham, Jubilee Campus Wollaton Road, NG8 1BB, Nottingham, UK

    Natalio Krasnogor

  3. Center for Cognitive and Neural Studies, Babes-Bolyai University of Cluj Napoca, (Coneural), Str. Ciresilor 29, 400487, Cluj-Napoca, Romania

    Dan Dumitrescu

  4. Department of Computer Science, Babes-Bolyai University, Kogalniceanu 1, 400084, Cluj-Napoca, Romania

    Camelia Chira

  5. Faculty of Economics and Business Administration, Babes-Bolyai University of Cluj Napoca, Str. Teodor Mihali Nr. 58-60, 400591, Cluj Napoca, Romania

    Rodica Lung

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Lung, R.I., Mihoc, T.D., Dumitrescu, D. (2011). Nash Extremal Optimization and Large Cournot Games. In: Pelta, D.A., Krasnogor, N., Dumitrescu, D., Chira, C., Lung, R. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2011). Studies in Computational Intelligence, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24094-2_14

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  • DOI: https://doi.org/10.1007/978-3-642-24094-2_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24093-5

  • Online ISBN: 978-3-642-24094-2

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