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In this course, we will study fundamental concepts in human-centered robotics, with an emphasis on mathematical models of human–robot interaction and decision-making algorithms for safely deploying robots in human-populated environments. We will ground these ideas in applications such as drones, autonomous vehicles, and home robots. After introducing the main technical tools for robot planning and control in interactive, safety-critical settings through a game-theoretic lens, we will turn our attention to two tightly coupled challenges in modern robotics: safely enabling robots that learn from humans and help humans learn. The course will combine seminar-style discussions of research papers and whiteboard-style lecture to introduce the key theoretical concepts, and the class project will give you an opportunity to explore the approaches covered in class and possibly combine them with your own research. After this class, you will be familiar with the state of the art and open challenges in safe and performant human–robot interaction, and you will understand the guarantees and tradeoffs offered by different algorithmic frameworks for human-centered robotics. Required student background: C/C++, data structures, calc III, linear algebra, probability. Students may receive credit for EN.601.497 or EN.601.697, but not both.