Skip to main content

Computation of Berge-Zhukovskii Equilibrium in Discrete Time Dynamic Games

  • Conference paper
  • First Online:
International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding (SOCO 2017, ICEUTE 2017, CISIS 2017)

Abstract

Berge-Zhukovskii equilibrium is an alternate solution concept to Nash equilibrium that induces cooperation in non-cooperative games. A solution of a game is a Berge-Zhukovskii equilibrium if the payoff of each player cannot increase regardless of what the other players do. The Berge-Zhukovskii equilibrium has been found to be us useful in trust games. We propose a new method, based on evolutionary algorithms, to detect and track the Berge-Zhukovskii equilibrium of a game considering a discrete-time dynamic environment. To test our method we propose a new dynamic multiplayer game model, based on the Voluntary contribution mechanism. Numerical results show the potential of 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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight 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

References

  1. Abalo, K., Kostreva, M.: Berge equilibrium: some recent results from fixed-point theorems. Appl. Math. Comput. 169, 624–638 (2005)

    MathSciNet  MATH  Google Scholar 

  2. Abalo, K.Y., Kostreva, M.M.: Intersection theorems and their applications to berge equilibria. Appl. Math. Comput. 182(2), 1840–1848 (2006)

    MathSciNet  MATH  Google Scholar 

  3. Bäck, T., Fogel, D., Michalewicz, Z. (eds.): Evolutionary Computation 1: Basic Algorithms and Operators. Institute of Physics Publishing, Bristol (2000)

    MATH  Google Scholar 

  4. Branke, J.: Evolutionary Optimization in Dynamic Environments. Kluwer Academic Publishers, Norwell (2001)

    MATH  Google Scholar 

  5. Colman, A.M., Korner, T.W., Musy, O., Tazdait, T.: Mutual support in games: some properties of Berge equilibria. J. Math. Psychol. 55(2), 166–175 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. Courtois, P., Nessah, R., Tazdat, T.: How to play games? Nash versus Berge behaviour rules. Econ. Philos. 31, 123–139 (2015). http://journals.cambridge.org/article_S026626711400042X

    Article  Google Scholar 

  7. Courtois, P., Nessah, R., Tazdat, T.: How to play games? Nash versus Berge behaviour rules. Econ. Philos. 31(1), 123–139 (2015)

    Article  Google Scholar 

  8. Das, S., Suganthan, P.: Differential evolution: a survey of the state-of-the-art. IEEE Trans. Evol. Comput. 15(1), 4–31 (2011)

    Article  Google Scholar 

  9. Gaskó, N., Dumitrescu, D., Lung, R.I.: Evolutionary detection of Berge and Nash equilibria. In: Pelta, D., Krasnogor, N., Dumitrescu, D., Chira, C., Lung, R. (eds.) Nature Inspired Cooperative Strategies for Optimization (NICSO 2011). Studies in Computational Intelligence, vol. 387, pp. 149–158. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  10. Hansen, N., Mller, S., Koumoutsakos, P.: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evol. Comput. 11(1), 1–18 (2003)

    Article  Google Scholar 

  11. Larbani, M., Nessah, R.: A note on the existence of Berge and Berge-Nash equilibria. Mathe. Soc. Sci. 55, 258–271 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  12. Lung, R.I., Dumitrescu, D.: Computing Nash equilibria by means of evolutionary computation. Int. J. of Comput. Commun. Control 3, 364–368 (2008)

    Google Scholar 

  13. Lung, R.I., Mihoc, T.D., Dumitrescu, D.: Nash equilibria detection for multi-player games. In: Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, pp. 1–5, 18–23 July 2010

    Google Scholar 

  14. Lung, R.I., Suciu, M., Gaskó, N., Dumitrescu, D.: Characterization and detection of Epsilon-Berge-Zhukovskii Equilibria. PLOS ONE 10(7), July 2015. e0131983

    Google Scholar 

  15. Musy, O., Pottier, A., Tazdait, T.: A new theorem to find berge equilibria. Int. Game Theory Rev. (IGTR) 14(01) (2012). 1250005-1-1

    Google Scholar 

  16. Nessah, R., Larbani, M., Tazdait, T.: A note on Berge equilibrium. Appl. Mathe. Lett. 20(8), 926–932 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  17. Storn, R., Price, K.: Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11(4), 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  18. Thomsen, R.: Multimodal optimization using crowding-based differential evolution. In: Proceedings of the 2004 IEEE Congress on Evolutionary Computation. pp. 1382–1389. IEEE Press, Portland (2004)

    Google Scholar 

  19. Zhukovskii, V.I., Chikrii, A.A.: Linear-quadratic differential games. Naukova Dumka, Kiev (1994)

    Google Scholar 

Download references

Acknowledgment

This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS - UEFISCDI, project number PN-II-RU-TE-2014-4-2560.

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

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Gaskó, N., Suciu, M.A., Lung, R.I. (2018). Computation of Berge-Zhukovskii Equilibrium in Discrete Time Dynamic Games. In: Pérez García, H., Alfonso-Cendón, J., Sánchez González, L., Quintián, H., Corchado, E. (eds) International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 León, Spain, September 6–8, 2017, Proceeding. SOCO ICEUTE CISIS 2017 2017 2017. Advances in Intelligent Systems and Computing, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-67180-2_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67180-2_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67179-6

  • Online ISBN: 978-3-319-67180-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics