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The coevolutionary ultimatum game on different network topologies

机译：不同网络拓扑上的协同进化最后通game博弈

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In this paper, a model of ultimatum game is discussed from the coevolutionary perspective, where strategy dynamics and structure dynamics coexist. The interplay between structure dynamics and strategy dynamics leads to overwhelmingly interesting evolved topology and fairness behaviors. It is found that fair division emerges for specific ratios of structure updating probability to strategy updating probability. Furthermore, it is shown that the initial structures have no essentially different effect on the coevolutionary results. In particular, the results for strategy are almost similar whenever the initial structure is set to be the nearest-neighbor coupled network, the ER random network or the scale-free network. Besides, the effects of other spatial factors are also investigated, e.g. the population size has a positive influence on the offer, while the average degree has a negative effect. In addition, one extrinsic factor, the background payoff, is also of great importance in promoting fair divisions. Apart from above, we study the properties of the evolved networks, which have the small-world effect and positive assortative behaviors.
机译：本文从协进化的角度讨论了最后通game博弈模型，其中策略动力学和结构动力学共存。结构动力学和策略动力学之间的相互作用导致了极为有趣的进化拓扑和公平行为。研究发现，对于结构更新概率与策略更新概率的特定比例，出现了公平的划分。此外，表明初始结构对协同进化结果没有本质上的不同影响。尤其是，无论何时将初始结构设置为最近邻居耦合网络，ER随机网络或无标度网络，策略的结果几乎都是相似的。此外，还研究了其他空间因素的影响，例如人口规模对报价有正面影响，而平均程度对报价有负面影响。此外，一个外在因素，即背景收益，在促进公平分配方面也非常重要。除此之外，我们研究了具有小世界效应和积极的分类行为的演化网络的性质。

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