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The Long-Term Benefits of Following Fairness Norms under Dynamics of Learning and Evolution

Lorini E., Mühlenbernd R.

Fundamenta Informaticae

2018

Vol. 158, nr 1/3

121--148

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 à 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. In a first step, 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. In a second step we transform the base game into a meta-game that represents a static description of a repeated game updated via fictitious play. We analyze such a meta-game under population dynamics by means of evolutionary game theory. Our results reveal two things: first of all, a great sensitivity to the fairness norm is beneficial in the long term when agents have the time to converge to mutual cooperation. Secondly, cooperativeness and fairness norm sensitivity can coevolve in a population of initially solely defectors.