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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)

Abstract

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.

Keywords

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.

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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

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