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

  • Enrico Gerding


  • David van Bragt


  • Han La Poutré


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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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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  1. Ariel Rubinstein, 2010. "Perfect Equilibrium in a Bargaining Model," Levine's Working Paper Archive 661465000000000387, David K. Levine.
  2. Costa-Gomes, Miguel & Zauner, Klaus G., 2001. "Ultimatum Bargaining Behavior in Israel, Japan, Slovenia, and the United States: A Social Utility Analysis," Games and Economic Behavior, Elsevier, vol. 34(2), pages 238-269, February.
  3. Shyam NMI Sunder & Haijin Lin, 2001. "Using Experimental Data to Model Bargaining Behavior in Ultimatum Games," Yale School of Management Working Papers ysm184, Yale School of Management.
  4. 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.
  5. 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.
  6. Riechmann, Thomas, 1997. "Learning and Behavoiral Stability - An Economic Interpretation of Genetic Algorithms," Hannover Economic Papers (HEP) dp-209, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  7. 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.
  8. 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.
  9. 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.
  10. Kalai, Ehud & Smorodinsky, Meir, 1975. "Other Solutions to Nash's Bargaining Problem," Econometrica, Econometric Society, vol. 43(3), pages 513-18, May.
  11. Ken Binmore & Nir Vulkan, 1999. "Applying game theory to automated negotiation," Netnomics, Springer, vol. 1(1), pages 1-9, October.
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