In this study we present a game-theoretic model of guilt in relation to sensitivity to norms of fairness. We focus on a specific kind of fairness norm `a la Rawls according to which a fair society should be organized so as to admit economic inequalities to the extent that they are beneficial to the less advantaged agents. We analyze the impact of the sensitivity to this fairness norm on the behavior of agents who play a repeated Prisoner’s Dilemma and learn via fictitious play. Our results reveal that a great sensitivity to the fairness norm is beneficial in the long term when agents have the time to converge to mutual cooperation.
CITATION STYLE
Lorini, E., & Mühlenbernd, R. (2015). The long-term benefits of following fairness norms: A game-theoretic analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9387, pp. 301–318). Springer Verlag. https://doi.org/10.1007/978-3-319-25524-8_19
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