Reinforcement Learning Theory

3 credits · College of Engineering catalogue

Advisory Prerequisite: ECE 501. Enforced Prerequisite: None. (3 credits) Basic theories and principles of reinforcement learning, and model-based and model-free reinforcement learning algorithms. Topics: Value iteration, policy iteration, Q-learning, SARSA, policy-gradient, variance reduction, linear and nonlinear function approximation, deep reinforcement learning, exploration-exploitation, convergence analysis, regret analysis.