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
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.