The aim of this book is to frame evolutionary game theory in the context of the science of complexity, providing at the same time an overview on some computational strategies for dealing with the related models. The second goal is to highlight the connections with statistical physics issues, e.g., the phenomenon of phase transitions, and to show how to use its tools, combined with other computational methods, for studying the dynamics of evolutionary game theory models. Therefore, the author decides to begin with a simple introductory chapter, followed by a second one focusing on some statistical physics methods. Moreover, the second chapter illustrates some computational methods for generating and analyzing complex networks, being a “tool” of great interest also in this area. Then, Chapters 3 and 4 illustrate practical cases, i.e., the structure of two famous games (Chapter 3), the prisoner’s dilemma and the public goods game, and two applications (Chapter 4), one framed in the context of social dynamics and the other in that of combinatorial optimization. Finally, a conclusive chapter summarizes some important concepts exposed in the previous chapters and provides a short overview on further developments. In this reviewer opinion a relevant missing topic is games on graphs:
[G. Szabó and G. Fáth, “Evolutionary games on graphs”, Phys. Rep. 446, No. 4–6, 97–216 (2006; doi:10.1016/j.physrep.2007.04.004)].