Foundations of RL

Explore the fundamentals of reinforcement learning in this comprehensive lecture from the Data-Driven Decision Processes Boot Camp. Delve into three key algorithms: TD learning, Q-Learning, and Natural Policy Gradient. Gain insights into the core concepts behind obtaining finite-time performance bounds for each algorithm. Building upon previous knowledge of Markov Decision Processes (MDPs), this talk provides a deeper understanding of reinforcement learning principles and their practical applications. Presented by Rayadurgam Srikant from the University of Illinois Urbana-Champaign, this hour-long session offers valuable knowledge for researchers and practitioners in the field of machine learning and decision-making processes.