Abstract
Hitherto, there has been an increasing interest in the ultimatum game, an elegant metaphor constituted for decoding the self-organization of fair behavior. Most previous studies have been done in the context of unbiased partner selection and symmetric role assignation. However, this is not always the case. To investigate the role of partner choice and role allocation on fairness, we develop a co-evolutionary ultimatum game in which agents can dynamically choose interacting neighbors as well as allocate game roles based on the real-time feedback from interactions. By the Monte Carlo simulation, we find that the related biases always play a crucial role in transforming the evolution of fairness. More specifically, the fairness level can be strikingly promoted when agents often aspire for interactions with more successful players and frequently designate reputable ones as proposers in the ultimatum game. For other cases, however, fairness is often remarkably inhibited. Compared with weak selection, strong selection turns out to be more favorable to the evolution of fair behavior. Finally, with proper parameters we witness the spontaneous emergence of social fairness in a totally self-regarding population under the noisy condition.
Published Version
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