This chapter introduces the concept of agent-based computational models (ABCMs) and their application in social science. The author, Joshua M. Epstein, argues that ABCMs provide a distinctive approach to social science, which he terms "generative." This approach is distinguished from both inductive and deductive methods by its focus on explaining the emergence of macroscopic regularities through the decentralized interactions of heterogeneous, autonomous agents. The chapter discusses the key features of ABCMs, including heterogeneity, autonomy, explicit space, local interactions, and bounded rationality. It highlights the potential of ABCMs for empirical research, interdisciplinary collaboration, and the study of connectionist social systems. Epstein also explores the implications of ABCMs for understanding the relationship between individual rationality and macroscopic equilibrium, and the decoupling of these concepts. The chapter concludes by discussing foundational issues, such as the computational characterization of social problems and the potential for hybrid analytical-computational approaches to non-equilibrium social systems.This chapter introduces the concept of agent-based computational models (ABCMs) and their application in social science. The author, Joshua M. Epstein, argues that ABCMs provide a distinctive approach to social science, which he terms "generative." This approach is distinguished from both inductive and deductive methods by its focus on explaining the emergence of macroscopic regularities through the decentralized interactions of heterogeneous, autonomous agents. The chapter discusses the key features of ABCMs, including heterogeneity, autonomy, explicit space, local interactions, and bounded rationality. It highlights the potential of ABCMs for empirical research, interdisciplinary collaboration, and the study of connectionist social systems. Epstein also explores the implications of ABCMs for understanding the relationship between individual rationality and macroscopic equilibrium, and the decoupling of these concepts. The chapter concludes by discussing foundational issues, such as the computational characterization of social problems and the potential for hybrid analytical-computational approaches to non-equilibrium social systems.