Leader Follower Game

Leader-follower games, also known as Stackelberg games, model hierarchical decision-making where leaders act first, influencing the choices of followers. Current research focuses on developing algorithms, such as those based on deep learning and online learning, to find optimal strategies in complex scenarios with multiple leaders and a single follower, or even partially observable interactions. These models find applications in diverse fields, including autonomous vehicle control (e.g., merging maneuvers) and financial modeling (e.g., investment strategies), where the ability to predict and react to the actions of others is crucial. The development of efficient and robust solution methods for these games is driving advancements in both theoretical game theory and practical applications.