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Subject offerings of new and developing areas of knowledge in aerospace engineering intended to augment existing formal courses. Topics and prerequisites vary for each section. See Class Schedule or departmental course information for both. Course Information: May be repeated in the same or separate terms if topics vary to a maximum of 12 hours.

Title: Learning and Control for Multi-Agent Systems In order for autonomous systems to become prevalent and integrated into the human life, robots need to interact with various intelligent agents including humans and other autonomous systems. In other words, robots need to perform in multi-agent settings. Our goal in this course is to discuss algorithms that allow autonomous systems to successfully operate in multi-agent scenarios including both cooperative and non-cooperative settings. This course is a graduate level course where we will study concepts and algorithms in control theory, game theory, and machine learning that have led to major progress in the state-of-the-art multi-agent robotic systems. Students will develop skills in evaluating research papers and are expected to conduct a final research project. 4 credit hours