Reinforcement Learning, Fall 2020

Rubric: AE 598RL and ME 598RL

Time: 10–11:50am, Tuesday and Thursday

Location: Remote (Zoom) - an invitation will be sent to all enrolled students

Instructors: Tim Bretl (research website) and Matt West (research website)

Description: Theory and practice of reinforcement learning as a tool for machine learning and artificial intelligence, applied to control, dynamics, and robotics, with a particular emphasis on computation. Topics will include reinforcement learning algorithms (temporal difference, Q-learning, policy gradient, actor-critic), function approximation and the use of deep neural networks, and efficient implementation on parallel architectures.


Coming soon!