CS 598 YL

Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

This course introduces students to recent developments in the field of robot learning. The curriculum begins with an overview of background material from relevant subfields, including computer vision, machine learning, robotics, and control theory. Next, the course delves into advanced techniques for advancing robots? capabilities, such as model-free reinforcement learning with function approximators, model learning and model-based RL, imitation learning, inverse reinforcement learning, self-supervised representation learning, and the integration of large foundational models. These advanced techniques will be examined through recent research papers that develop and validate them. The course concludes with case studies on robotic manipulation and navigation from recent research. Participating in project work as part of the course will offer students an insight into research in this emerging field. Prerequisites: Understanding of basic concepts in artificial intelligence and machine le