Coevolution of spatial ultimatum game and link weight promotes fairness

Lili Deng, Xingxing Zhang and Cheng Wang

Applied Mathematics and Computation, 2021, vol. 392, issue C

Abstract: In real life, individuals have the capacity to adjust their social relationships on network according to the feedback of their communication. Based on this fact, we present a coevolutionary ultimatum game model to explore the role of dynamic interaction on fairness, in which the link weight is introduced to represent the strength of the social relationship and the link weight is dynamically updated by comparing payoff received via the interaction with the weighted average utility. We mainly analyze the effects of link weight boundary control parameter and link weight adjustment amplitude on the evolution of fairness. Through Monte Carlo simulations, we find that the coevolutionary mechanism of game strategy and link weight can promote the emergence of fairness. More specifically, the fairness is strikingly promoted with the increase of the link weight boundary control parameter, while the influence of link weight adjustment amplitude is not so significant. Moreover, the introduction of this coevolutionary mechanism results in heterogeneous link weight distribution, and the larger link weight boundary control parameter can generate a higher network heterogeneity.

Keywords: Fairness; Ultimatum game; Coevolution; Dynamic weighted network; Link weight (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:392:y:2021:i:c:s0096300320306512

DOI: 10.1016/j.amc.2020.125698

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