This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

Introduction The moment I felt the most cold sweat in my machine learning career was during an internal review when I was ...

Sequential decision-making under uncertainty is a foundational topic in multiple fields - including economics, operations research, and computer science, built around the foundation of Markov decision ...

Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a cornerstone of intelligence for machines and living ...