BVA 529E - Reinforce.Lear.for Busi.App.

Course Objectives

1. To introduce theory of Markov decision problems and reinforcement learning
2. To introduce different reinforcement learning techniques
3. To implement different reinforcement learning techniques to various problems
4. To introduce performance evaluation of reinforcement learning techniques

Course Description

This course provides an introduction to some of the foundational ideas of reinforcement learning, including Markov decision processes, value functions, Monte Carlo estimation, dynamic programming, temporal difference learning, eligibility traces, and function approximation. However, we will also cover additional material drawn from the latest deep Reinforcement Learning literature. Programming assignments and projects will require implementing and testing these techniques for various problems.