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Multi-Issue Negotiation Processes by Evolutionary Simulation, Validation and Social Extensions

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  • Enrico Gerding

    ()

  • David van Bragt

    ()

  • Han La Poutré

    ()

Abstract

We describe a system for bilateral negotiations in which artificial agents aregenerated by an evolutionary algorithm (EA). The negotiations are governed bya finite-horizon version of the alternating-offers protocol. Several issuesare negotiated simulataneously. We first analyse and validate the outcomes ofthe evolutionary system, using the game-theoretic subgame-perfect equilibriumas a benchmark. We then present two extensions of the negotiation model. Inthe first extension agents take into account the fairness of the obtainedpayoff. We find that when the fairness norm is consistently applied during thenegotiation, agents reach symmetric outcomes which are robust and ratherinsensitive to the actual fairness settings. In the second extension we modela competitive market situation where agents have multiple bargainingopportunities before reaching the final agreement. Symmetric outcomes are nowalso obtained, even when the number of bargaining opportunities is small. Wefurthermore study the influence of search or negotiation costs in this game. Copyright Kluwer Academic Publishers 2003

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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 22 (2003)
Issue (Month): 1 (August)
Pages: 39-63

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Handle: RePEc:kap:compec:v:22:y:2003:i:1:p:39-63

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Web page: http://www.springerlink.com/link.asp?id=100248
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Keywords: multi-issue bargaining; evolutionary algorithms; fairness; multiple bargaining opportunities; game theory;

References

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  1. Riechmann, Thomas, 1997. "Learning and Behavoiral Stability - An Economic Interpretation of Genetic Algorithms," Hannover Economic Papers (HEP) dp-209, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  2. Rubinstein, Ariel, 1982. "Perfect Equilibrium in a Bargaining Model," Econometrica, Econometric Society, vol. 50(1), pages 97-109, January.
  3. Alvin E. Roth & V. Prasnikar & M. Okuno-Fujiwara & S. Zamir, 1998. "Bargaining and market behavior in Jerusalem, Liubljana, Pittsburgh and Tokyo: an experimental study," Levine's Working Paper Archive 344, David K. Levine.
  4. Harrison, Glenn W & McCabe, Kevin A, 1996. "Expectations and Fairness in a Simple Bargaining Experiment," International Journal of Game Theory, Springer, vol. 25(3), pages 303-27.
  5. Ken Binmore & Nir Vulkan, 1999. "Applying game theory to automated negotiation," Netnomics, Springer, vol. 1(1), pages 1-9, October.
  6. Roth, Alvin E & Murnighan, J Keith & Schoumaker, Francoise, 1988. "The Deadline Effect in Bargaining: Some Experimental Evidence," American Economic Review, American Economic Association, vol. 78(4), pages 806-23, September.
  7. Kalai, Ehud & Smorodinsky, Meir, 1975. "Other Solutions to Nash's Bargaining Problem," Econometrica, Econometric Society, vol. 43(3), pages 513-18, May.
  8. Shyam Sunder & Haijin Lin, 2003. "Using Experimental Data to Model Bargaining Behavior in Ultimatum Games," Yale School of Management Working Papers ysm330, Yale School of Management.
  9. Binmore, K & Shaked, A & Sutton, J, 1985. "Testing Noncooperative Bargaining Theory: A Preliminary Study," American Economic Review, American Economic Association, vol. 75(5), pages 1178-80, December.
  10. Miguel Costa-Gomes & Klaus G. Zauner, . "Ultimatum Bargaining Behavior in Israel, Japan, Slovenia and the United States: A Social Utility Analysis," Discussion Papers 00/37, Department of Economics, University of York.
  11. Weg, Eythan & Rapoport, Amnon & Felsenthal, Dan S., 1990. "Two-person bargaining behavior in fixed discounting factors games with infinite horizon," Games and Economic Behavior, Elsevier, vol. 2(1), pages 76-95, March.
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Cited by:
  1. D.D.B. Bragt, van & J. A. La Poutr & E. H. Gerding, 2000. "Equilibrium Selection In Evolutionary Bargaining Models," Computing in Economics and Finance 2000 323, Society for Computational Economics.
  2. Waltman, L. & van Eck, N.J.P. & Dekker, R. & Kaymak, U., 2009. "Economic Modeling Using Evolutionary Algorithms: The Effect of a Binary Encoding of Strategies," ERIM Report Series Research in Management ERS-2009-028-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
  3. D.D.B. van Bragt and J.A. La Poutre, 2001. "Evolving Automata Negotiate with a Variety of Opponents," Computing in Economics and Finance 2001 118, Society for Computational Economics.
  4. Herbert Dawid & Joern Dermietzel, 2006. "How Robust is the Equal Split Norm? Responsive Strategies, Selection Mechanisms and the Need for Economic Interpretation of Simulation Parameters," Computational Economics, Society for Computational Economics, vol. 28(4), pages 371-397, November.

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