进化博弈论中的复制动力学的典型框架假设所有突变都是同样可能的,这意味着不断发展的居民的突变只会不断做出贡献。然而,在生物和社会科学的自然系统中,突变可能由于其重复再生而产生。改变策略(更新)的现象,通常延长序列重复多次,被定义为进化博弈论中被忽视的波动突变。实施重复的时间框架引入了与成对费米规则结合的动态突变方面。网络结构,在许多自然和人工系统中无处不在,显著影响了进化博弈的动态和结果。我们从困境强度的角度研究了成对博弈的演变。揭示了突变强度可以影响进化动力学。我们还证明了通过确定性和多主体模拟(MAS)过程运行的结果对于线性和非线性动力学都具有相似的稳定区域,甚至在各种游戏类。特别是,对于合作的分数与突变个体的分数之间的关系,检测到最刺激的效果,在相反的情况下,倾斜倾向于提供增加的趋势和支持叛变。总之,我们确定了一种形式的挥发性突变作为一种形式的噪声,在某些情况下,可用于加强社会系统中的合作,并设计促进网络环境中合作的策略。
The typical framework of replicator dynamics in evolutionary game theory assumes that all mutations are equally likely, meaning that the mutation of an evolving inhabitant only contributes constantly. However, in natural systems in biological and social sciences, mutations can arise due to their repetitive regeneration. The phenomenon of changing strategies (updating), typically prolonged sequences repeated many times, is defined as a volatile mutation that has been overlooked in evolutionary game theory. Implementing a repeated time framework introduces a dynamic mutation aspect incorporated with the pairwise Fermi rule. Network structure, ubiquitous in many natural and artificial systems, has significantly affected the dynamics and outcomes of evolutionary games. We examine the evolution of the pairwise game in terms of dilemma strength. It is revealed that mutation intensity can influence evolutionary dynamics. We also demonstrated that the obtained outcomes run by the deterministic and multi-agent simulation (MAS) process present similar stability regions for both linear and non-linear dynamics, even in various game classes. In particular, the most stimulating effect is detected for the relationship between the fraction of cooperation and the fraction of the mutated individuals, as inclination tends to provide an increasing tendency and supporting defection in the opposite case. In conclusion, we identified a form of volatile mutation as a form of noise that, under certain situations, could be used to enhance cooperation in social systems and design strategies for promoting cooperation in networked environments.