Randomness and Arbitrary Coordination in the Reactive Ultimatum Game
Roberto da Silva, Pablo A. Valverde, Luis C. Lamb

TL;DR
This paper investigates a reactive version of the ultimatum game where acceptance depends on offers, analyzing mean field and networked populations to understand how fairness and cooperation emerge through evolutionary dynamics.
Contribution
It introduces and analyzes a reactive ultimatum game model with acceptance probability depending on offers, exploring convergence to fairness in mean field and networked populations.
Findings
Reactive acceptance influences convergence to fair splits.
Network structure affects bargaining outcomes.
Polices impact population cooperation and fairness.
Abstract
Darwin's theory of evolution - as introduced in game theory by Maynard Smith - is not the only important evolutionary aspect in a evolutionary dynamics, since complex interdependencies, competition, and growth should be modeled by, for example, reactive aspects. In the ultimatum game the reciprocity and the fifty-fifty partition seems to be a deviation from rational behavior of the players under the light of the Nash equilibrium concept.Such equilibrium emerges, for example, from the punishment of the responder who generally tends to refuse unfair proposals. In the iterated version of the game, the proposers are able to improve their proposals by adding a value thus making fairer proposals. Such evolutionary aspects are not properly Darwinian-motivated, but they are endowed with a fundamental aspect: they reflect their actions according to value of the offers. Recently, a reactive…
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