@inbook{fa7cc5255aca48afbb3745f84d0d8de8,

title = "Evolutionary graph theory",

abstract = "Evolutionary graph theory (EGT), studies the ability of a mutant gene to overtake a finite structured population. In this chapter, we describe the original framework for EGT and the major work that has followed it. Here, we will study 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.",

keywords = "Evolutionary stability, Large graph, Payoff matrix, Regular graph, Undirected graph",

author = "Paulo Shakarian and Abhinav Bhatnagar and Ashkan Aleali and Elham Shaabani and Ruocheng Guo",

note = "Publisher Copyright: {\textcopyright} 2015, The Author(s).",

year = "2015",

doi = "10.1007/978-3-319-23105-1_6",

language = "English (US)",

series = "SpringerBriefs in Computer Science",

publisher = "Springer",

number = "9783319231044",

pages = "75--91",

booktitle = "SpringerBriefs in Computer Science",

edition = "9783319231044",

}