Tanimoto Jun
Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga-koen, Kasuga-shi, Fukuoka 816-8580, Japan.
Phys Rev E Stat Nonlin Soft Matter Phys. 2014 Jan;89(1):012106. doi: 10.1103/PhysRevE.89.012106. Epub 2014 Jan 8.
Network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium in 2 × 2 prisoner's dilemma games. Previous studies have shown that cooperation can be enhanced by using a skewed, rather than a random, selection of partners for either strategy adaptation or the gaming process. Here we show that combining both processes for selecting a gaming partner and an adaptation partner further enhances cooperation, provided that an appropriate selection rule and parameters are adopted. We also show that this combined model significantly enhances cooperation by reducing the degree of activity in the underlying network; we measure the degree of activity with a quantity called effective degree. More precisely, during the initial evolutionary stage in which the global cooperation fraction declines because initially allocated cooperators becoming defectors, the model shows that weak cooperative clusters perish and only a few strong cooperative clusters survive. This finding is the most important key to attaining significant network reciprocity.
网络互惠是增加社会粘性的一种机制,它能在2×2囚徒困境博弈中实现合作均衡。先前的研究表明,在策略适应或博弈过程中,通过非随机而是偏向性地选择合作伙伴,可以增强合作。本文表明,只要采用适当的选择规则和参数,将选择博弈伙伴和适应伙伴这两个过程结合起来,能进一步增强合作。我们还表明,这种组合模型通过降低底层网络的活跃度来显著增强合作;我们用一个称为有效度的量来衡量活跃度。更确切地说,在初始进化阶段,由于最初分配的合作者变成背叛者,全球合作比例下降,该模型显示弱小的合作集群会消亡,只有少数强大的合作集群得以幸存。这一发现是实现显著网络互惠的最重要关键。