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Emergence of Fair Offers in Ultimatum Game

  • Wanting Xiong
  • Han Fu
  • Yougui WangEmail author
Chapter
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Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 669)

Abstract

The dynamics of how fair offers come about in ultimatum game is studied via the method of agent-based modeling. Both fairness motive and adaptive learning are considered to be important in the fair behavior of human players in concerning literature. Here special attention is paid to situations where adaptive learning proposers encounter responders with either pure money concern or fairness motivation. The simulation results show that the interplay of adaptive learning participants yields a perfect sub-game equilibrium, but fair offers will be provided by proposers as long as a small proportion of responders play “tough” against unfair offer.

Keywords

Adaptive Learning Subgame Perfect Equilibrium Ultimatum Game Monetary Loss Human Player 
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.

Notes

Acknowledgements

We are grateful to Dr. Jianzhong Zhang for his suggestions and language improvements. This research was supported by National Natural Science Foundation of China under Grant of No. 61174165 and Program for New Century Excellent Talents in University (NCET-10-0245). This work was also the result of Interdisciplinary Salon of Beijing Normal University.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Systems Science, School of ManagementBeijing Normal UniversityBeijingPeople’s Republic of China

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