Artificial Intelligence for Robotics

This course explores the foundations of artificial intelligence (AI) with an emphasis on robotics and decision-making in complex environments. Topics include search algorithms, constraint satisfaction, probabilistic models, planning under uncertainty, and machine learning. Students also study multi-agent systems and game-theoretic reasoning, learning how intelligent agents interact, cooperate, or compete in shared environments. Applications are grounded in robotics, with examples such as navigation, localization, and autonomous decision-making. By the end of the course, students gain a solid understanding of how AI enables robots to perceive the world, make decisions, and adapt in multi-agent and dynamic settings.

The relevant course materials are provided below, along with a sample set of slides for reference.