Stackelberg Planning

Stackelberg planning models strategic interactions where a leader anticipates and influences the actions of a follower, aiming to achieve a desired outcome. Current research focuses on developing efficient algorithms for solving these games, particularly in complex scenarios with multiple leaders and followers, nonlinear dynamics, and imperfect information, often employing iterative methods and potential game frameworks. This approach finds applications in diverse fields like robotics, manufacturing, and autonomous systems, improving coordination, resource allocation, and overall system performance by leveraging strategic decision-making. The theoretical complexity of Stackelberg planning is also under investigation, seeking to identify tractable problem instances and efficient solution methods.