On Fairness in an Alternating-Offers Bargaining Model with Evolutionary Agents

  • Norberto Eiji Nawa
  • Katsunori Shimohara
  • Osamu Katai
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2132)


The emergence of agents that play fair strategies is investigated in a simple bargaining model. The strategies played by the agents are constructed by evolutionary algorithms. Agents make offers to each other describing possible ways to share a certain commodity, until an offer is accepted. Finite-horizon bargaining models give an advantage to the first or last part making an offer, depending on the discount factor incurred by the players in each transaction. By introducing uncertainty regarding the playing order, i.e., who makes the first or last offers, experimental results show that evolutionary agents abandon greedy strategies, that attempt to obtain the whole commodity without sharing, for those that lead to more just divisions of the commodity.


Evolutionary Algorithm Discount Factor Negotiation Process Average Strategy Ultimatum Game 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    W. B. Arthur, J. H. Holland, B. LeBaron, R. Palmer, and P. Tayler. Asset pricing under endogenous expectations in an artificial stock market. In W. B. Arthur, S. N. Durlauf, and D. A. Lane, editors, The Economy as an Evolving Complex System II, pages 15–44. Addison-Wesley, 1997.Google Scholar
  2. 2.
    T. Bäck, G. Rudolph, and H.-P. Schwefel. Evolutionary programming and evolution strategies: Similarities and differences. In D. B. Fogel and W. Altmar, editors, Proc. the 2nd Annual Evolutionary Programming Conference, pages 11–22, February 1992.Google Scholar
  3. 3.
    K. Binmore. Game Theory and the Social Contract-Volume 2: Just Playing. MIT Press, 1998.Google Scholar
  4. 4.
    K. Binmore, A. Shaked, and J. Sutton. Testing noncooperative bargaining theory: A preliminary study. American Economic Review, 75(5):1178–1180, December 1985.Google Scholar
  5. 5.
    G. E. Bolton. The rationality of splitting equally. Journal of Economic Behavior and Organization, 32:365–381, 1997.CrossRefGoogle Scholar
  6. 6.
    C. Boutilier, Y. Shoham, and M. P. Wellman, editors. Artifical Intelligence, volume 94(1–2). Elsevier, July 1997. Special Issue on Economic Principles of Multi-Agent Systems.Google Scholar
  7. 7.
    R. Forsythe, J. L. Horowitz, N. E. Savin, and M. Sefton. Fairness in simple bargaining experiments. Games and Economic Behavior, 6:347–369, 1994.zbMATHCrossRefGoogle Scholar
  8. 8.
    E. H. Gerding, D. D. B. van Bragt, and J. A. L. Poutré. Multi-issue negotiation processes by evolutionary simulation: Validation and social extensions. Technical Report SEN R0024, CWI, Centre for Mathematics and Computer Science, 2000.Google Scholar
  9. 9.
    J. C. Harsanyi. Rational Behavior and Bargaining Equilibrium in Games and Social Situations. Cambridge University Press, 1977. Paperback edition: 1986.Google Scholar
  10. 10.
    J. O. Kephart, J. E. Hanson, and J. Sairamesh. Price and niche wars in a free-market economy of software agents. Artificial Life, 4(1):1–23, 1998.CrossRefGoogle Scholar
  11. 11.
    N. Matos, C. Sierra, and N. R. Jennings. Determining successful negotiation strategies: An evolutionary approach. In Proc. 3rd Int. Conf. on Multi-Agent Systems (ICMAS 98), pages 182–189, 1998.Google Scholar
  12. 12.
    A. Muthoo. Bargaining Theory with Applications. Cambridge University Press, 1999.Google Scholar
  13. 13.
    J. Neelin, H. Sonnenschein, and M. Spiegel. A further test of noncooperative bargaining theory: Comment. American Economic Review, 78(4):824–836, September 1988.Google Scholar
  14. 14.
    J. Ochs and A. E. Roth. An experimental study of sequential bargaining. American Economic Review, 79(3):355–384, June 1989.Google Scholar
  15. 15.
    J. R. Oliver. On Artificial Agents for Negotiation in Electronic Commerce. PhD thesis, University of Pennsylvania, 1996.Google Scholar
  16. 16.
    J. Rawls. A Theory of Justice. Belknap Press, 1999. Revised Edition.Google Scholar
  17. 17.
    J. S. Rosenschein and G. Zlotkin. Rules of Encounter: Designing Conventions for Automated Negotiation among Computers. MIT Press, 1994.Google Scholar
  18. 18.
    A. Rubinstein. Perfect equilibrium in a bargaining model. Econometrica, 50(1):97–109, January 1982.Google Scholar
  19. 19.
    T. J. Sargent. Bounded Rationality in Macroeconomics. Oxford University Press, 1993.Google Scholar
  20. 20.
    H. A. Simon. Models of Bounded Rationality: Behavioral Economics and Business Organization, volume 2. MIT Press, 1982.Google Scholar
  21. 21.
    R. H. Thaler. The ultimatum game. Journal of Economic Perspectives, 2(4):195–206, 1989.Google Scholar
  22. 22.
    D. D. B. van Bragt, E. H. Gerding, and J. A. L. Poutré. Equilibrium selection in alternating-offers bargaining models: The evolutionary computing approach. In 6 th Int. Conf. of the Society for Computational Economics on Computing in Economics and Finance (CEF’2000), July 2000.Google Scholar
  23. 23.
    H. R. Varian. Economic mechanism design for computerized agents. In Proceedings of the First Usenix Conference on Electronic Commerce. July 1995.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Norberto Eiji Nawa
    • 1
    • 2
  • Katsunori Shimohara
    • 1
    • 2
  • Osamu Katai
    • 2
  1. 1.ATR International - Information Sciences DivisionKyotoJapan
  2. 2.Dept. of Systems Science, Graduate School of InformaticsKyoto UniversityKyotoJapan

Personalised recommendations