EE 383: Reinforcement Learning: Behaviors and Applications (MS&E 235B)

Course Description

The subject of reinforcement learning addresses the design of agents that improve decisions over time while operating within complex environments. This course covers desired agent behaviors and principled scalable approaches to realizing such behavior. Homework assignments primarily involve programming exercises carried out in Colab. Prerequisites: EE 277 / MS&E237A, machine learning (e.g., EE 104/ CME 107, MS&E 226, or CS 229).