CMSC818B

Restricted to Computer Science students (CMSC) or permissin of instructor. Motion planning focuses on the problem of how to go from point A to point B. In this course, we will examine higher-level algorithms that make decisions as to what points A and B should be depending on the task at hand. Topics that will be covered include (but are not limited to): Markov Decision Processes; Partially Observable Markov Decision Processes; Monte-Carlo Tree Search; Deep reinforcement learning; Graph Neural Networks; Multi-Robot Task Assignment; Vehicle Routing Problems; Information-Theoretic Path Planning (mutual information, entropy, submodularity).