Description
Reinforcement learning is a subfield of machine learning focused on discovering ‘optimal policies’: robust strategies to achieve a desired objective under varying states of the world. In this talk, we will provide an overview of terminology in reinforcement learning and sample Python programs for basic algorithms to learn policies. We will also discuss the state of the art in reinforcement learning and the ways in which reinforcement learning can be applied to real world problems.