This chapter provides a detailed formulation of the modeling framework for analyzing strategic interactions in large populations of decision-making agents. The focus is on collective behaviors that arise from asynchronous, uncertain, and boundedly rational decision-making processes in a non-cooperative environment. To study the temporal evolution of these behaviors, two interconnected deterministic approximations are introduced: the evolutionary dynamics model (EDM), describing the evolution of the strategic distribution, and the payoff dynamics model (PDM), capturing the dynamics of perceived payoffs. Together, these models form a closed-loop system whose properties determine the existence and convergence toward generalized Nash equilibria, which represent stable and feasible long-term outcomes. The chapter also formalizes the notion of control within this framework, draws parallels with optimization, and illustrates the concepts with examples and simulations.