Quantifying fairness to overcome selfishness: A behavioural model to describe the evolution and stabilization of inter-group bias using the Ultimatum Game
Authored by Andrea Guazzini, Enrico Imbimbo, Federica Stefanelli, Franco Bagnoli, Ezio Venturino
Date Published: 2019
DOI: 10.3934/mbe.2019184
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Abstract
The ability to form groups to overcome problems has been crucial for the
evolution of human beings. To favour the formation of cooperating
groups, one of the mechanisms developed is the inter-group bias, namely
the tendency of individuals to favour members of their group and hinder
the external ones. It is the cognitive equivalent of the ``green beard
effect{''} in evolutionary biology, introduced by Hamilton and
popularized by Dawkins, for which a group can profit of the altruistic
behaviour of its members. Here, we use a behavioural model based on the
Ultimatum Game, to shed light on how this behaviour cloud has been
stabilized in the human population, estimating the magnitude of
favouritism needed to overcome selfish individuals. Through both
numerical simulations and analytic approaches, we study how a community
of collectivist and individualist agents evolves. The key factor is the
mechanism for the evolution of the population, i.e., the replacement of
the poor-performing individuals. In the case of replacement by the
reproduction of existing individuals, we observe a smooth phase
transition and no coexistence. If the replacement is random, the
transition smooths, and coexistence is possible. We developed analytical
approaches for these two cases and performed numerical simulations.
Although analytical calculations support the behaviour emerging from
simulations, some differences ask for more refined treatments.
Tags
Agent-based modeling
Evolution
Cooperation
Fairness
Ultimatum game
mathematical models
Decision-Making
Dynamical systems
Indirect reciprocity
Inter-group favouritism
Selfishness
Stakes