The paper introduces evolutionary games as models for repeated anonymous strategic interactions, where actions or behaviors that are more "fit" tend to displace less fit behaviors over time. The author, Daniel Friedman, focuses on the dynamics of these games and their relationship to static equilibria such as Nash equilibrium (NE) and evolutionary stable state (ESS). Key concepts include fitness functions and compatible dynamics, which are illustrated through numerical examples. Cone fields are introduced to characterize continuous-time dynamical processes compatible with a given fitness function. The analysis centers on dynamic steady-state equilibria and their connection to static equilibria. It is shown that all stable dynamic steady states are NE, and all NE are dynamic steady states for large classes of dynamics. However, ESS is less closely related to dynamic equilibria. The paper concludes with a survey of economic applications of evolutionary games.The paper introduces evolutionary games as models for repeated anonymous strategic interactions, where actions or behaviors that are more "fit" tend to displace less fit behaviors over time. The author, Daniel Friedman, focuses on the dynamics of these games and their relationship to static equilibria such as Nash equilibrium (NE) and evolutionary stable state (ESS). Key concepts include fitness functions and compatible dynamics, which are illustrated through numerical examples. Cone fields are introduced to characterize continuous-time dynamical processes compatible with a given fitness function. The analysis centers on dynamic steady-state equilibria and their connection to static equilibria. It is shown that all stable dynamic steady states are NE, and all NE are dynamic steady states for large classes of dynamics. However, ESS is less closely related to dynamic equilibria. The paper concludes with a survey of economic applications of evolutionary games.