Society is rapidly evolving at the whims of cultural shifts and technological advancement, leading to systems that are driven by decision-makers with various types of capabilities, behaviors, and incentives. This emergent heterogeneity is now a defining feature that governs the modern world, yet its impact is poorly understood at a scientific level. How will societal outcomes unfold when everyone has an abundance of information and AI tools at their fingertips? Will these outcomes be for the better? This CAREER project seeks to shed light on how and when decision-making at a large scale can avoid bad, or tragic, outcomes. The intellectual merit of the project includes the development of theoretical frameworks that are well-equipped to analyze the benefits and impacts of AI tools to the society. The broader impacts of the project include generating new approaches for solving collective action problems that arise in the society, such as the management of common resources and epidemics. Moreover, this project will develop a new course on agent-based simulations that will be made accessible to all students on campus. It will also include K-12 outreach activities as well as the involvement of undergraduate researchers. The project focuses on studying multi-agent systems driven by large numbers of agents that interact with dynamic environments and learn to make decisions over time. The proposed research will build and validate new mathematical frameworks at the intersection of evolutionary game theory and control systems to address the challenges associated with predicting and influencing collective behavior. This effort represents fundamental extensions to existing analyses, which primarily focus on dynamics where agents obey simple learning rules. The project represents a unified effort to understand the impact that a wider range of more complex agent learning has on societal systems, such as the utilization of common resources and epidemics. A persisting question in