Teaching Assistant - DDA4230

This course is a basic introduction to reinforcement learning algorithms and their applications. Topics include: multi-armed bandits; finite Markov decision processes; dynamic programming; Monte Carlo methods; temporal-difference learning; actor-critic methods; off-policy learning; and introduction to approximation methods.