-Provides an overview of the book and introduces the concept of agent-based modeling in the context of evolutionary game dynamics and introduces the reader to the basics of agent-based modeling and evolutionary game dynamics.

-Explores the behaviour of agents when they are connected in a network rather than a grid. This chapter examines the impact of different revision protocols and payoff functions on the behavior of agents.

-Focuses on the formation of networks as an endogenous process that arises from the interactions among agents and also deals with games involving more than two populations.

-Introduces a technique for solving the mean dynamics of a system at runtime also provides a summary of the models presented in the book, including their key features and results.

-It is primarily aimed at researchers, students, and professionals interested in the fields of game theory, evolutionary dynamics, and agent-based modeling. It is also relevant to those working in related areas such as computational social science, artificial intelligence, and complexity science.