6.884 Learning for Control / Computational Sensorimotor Learning


Graduate Level; AUS, II
Units: 3-0-9
Prerequisites: 6.036, 6.867, or permission of instructor
Instructor:  Professor Pulkit Agrawal
Schedule:  TR11-12:30, virtual instruction
This subjects qualifies as an Artificial Intelligence concentration subject.
Introduces the fundamental algorithmic approaches for constructing agents that learn to act in their environment from raw sensory observations. Topics include imitation learning, observation learning, self-supervised learning, reinforcement learning, inverse reinforcement learning, model learning from raw sensory observations. The course will also provide an overview of practical learning based approached used for navigation and robotic manipulation. A significant portion of the course will be devoted to reading research papers.