Shakarian Paulo, Roos Patrick, Johnson Anthony
Network Science Center and Dept. of Electrical Engineering and Computer Science, United States Military Academy, West Point, NY 10996, United States.
Biosystems. 2012 Feb;107(2):66-80. doi: 10.1016/j.biosystems.2011.09.006. Epub 2011 Oct 12.
Evolutionary graph theory (EGT), studies the ability of a mutant gene to overtake a finite structured population. In this review, we describe the original framework for EGT and the major work that has followed it. This review looks at the calculation of the "fixation probability" - the probability of a mutant taking over a population and focuses on game-theoretic applications. We look at varying topics such as alternate evolutionary dynamics, time to fixation, special topological cases, and game theoretic results. Throughout the review, we examine several interesting open problems that warrant further research.
进化图论（EGT）研究突变基因在有限结构化种群中占据主导地位的能力。在这篇综述中，我们描述了EGT的原始框架以及在此之后的主要研究工作。这篇综述着眼于“固定概率”的计算——即突变体占据种群的概率，并重点关注博弈论应用。我们探讨了各种不同的主题，如交替进化动力学、固定时间、特殊拓扑情况以及博弈论结果。在整个综述过程中，我们研究了几个值得进一步研究的有趣的开放性问题。
