Undergraduate Prerequisites: Multivariate Calculus (MA 225), Linear Algebra (EK 103), Probability (EK 381), and Programming (EK 128, Python experience is highly recommended), Machine Learning (EC 414). - This class will discuss recent developments in machine learning and perception for robotics. Specifically, we will study advanced concepts in perception and decision-making algorithms in order to provide theoretical and experimental frameworks for robot learning. Topics will include 3D vision, sensorimotor paradigms for perception and action, robot reinforcement learning, imitation learning, inverse reinforcement learning, exploration, options, model-based approaches, POMDP and human-machine and social interaction.

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