Emergence of Fair Offers in Ultimatum Game
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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.
KeywordsAdaptive Learning Subgame Perfect Equilibrium Ultimatum Game Monetary Loss Human Player
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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