Skip to main content

Strong Berge and Strong Berge Pareto Equilibrium Detection Using an Evolutionary Approach

  • Chapter
Applied Computational Intelligence in Engineering and Information Technology

Part of the book series: Topics in Intelligent Engineering and Informatics ((TIEI,volume 1))

  • 633 Accesses

Abstract

Nash equilibrium is an important solving concept in Game Theory. Playing in Nash sense means that no player can deviate from the equilibrium strategy in order to increase her/his payoff. Some games can have several Nash equilibria. Strong Berge and strong Berge Pareto equilibria are important refinements of the Nash equilibrium. An evolutionary technique based on non-domination is proposed in order to detect the strong Berge and strong Berge Pareto equilibria. Some numerical experiments are presented in order to illustrate the proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Gintis, H.: The bounds of reason, game theory and the unification of the behavioral sciences. Princeton University Press (2009)

    Google Scholar 

  2. Osborne, M.: An introduction to game theory. Oxford University Press, New York (2004)

    Google Scholar 

  3. Nash, J.F.: Non-cooperative games. Ann. Math. 54, 286–295 (1951)

    Article  MathSciNet  MATH  Google Scholar 

  4. Berge, C.: Theorie generale des jeux a n-persones. Gauthier-Villars, Paris (1957)

    Google Scholar 

  5. Nessah, R., Tazdait, T., Larbani, M.: Strong Berge and Pareto equilibrium existence for a non-cooperative game. Working Paper (2008)

    Google Scholar 

  6. Lung, R.I., Dumitrescu, D.: Computing Nash equilibria by means of evolutionary computation. Int. J. Comp. Communic. Control III, 364–368 (2008)

    Google Scholar 

  7. Dumitrescu, D., Lung, R.I., Gaskó, N., Mihoc, T.D.: Evolutionary detection of Aumann equilibrium. In: Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2010), Portland, OR, USA, pp. 827–828 (2010)

    Google Scholar 

  8. Dumitrescu, D., Lung, R.I., Gaskó, N.: Detecting strong Berge Pareto equilibrium in a non-cooperative game using an evolutionary approach. In: Proceedings of 6th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI 2011), Timisoara, Romania, pp. 101–104 (2011)

    Google Scholar 

  9. Deb, K., Agrawa, S., Pratab, A., Meyarivan, T.: A fast elitist Non-dominated Sorting Genetic Algorithm for multi-objective optimization: NSGA-II. In: Proceedings of the Parallel Problem Solving from Nature VI Conference, Paris, France, pp. 849–858 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Noémi Gaskó .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag GmbH Berlin Heidelberg

About this chapter

Cite this chapter

Gaskó, N., Lung, R.I., Dumitrescu, D. (2012). Strong Berge and Strong Berge Pareto Equilibrium Detection Using an Evolutionary Approach. In: Precup, RE., Kovács, S., Preitl, S., Petriu, E. (eds) Applied Computational Intelligence in Engineering and Information Technology. Topics in Intelligent Engineering and Informatics, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28305-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28305-5_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28304-8

  • Online ISBN: 978-3-642-28305-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics