In this talk, I will start by describing the main settings where machine learning is of interest.
I will then focus on the reinforcement learning (RL) setting that deals with sequential decision-making tasks. In particular, I will describe how the combination of RL and deep learning (deep RL) has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine.
Vincent Francois-Lavet is a researcher in machine learning and the author of an introductory book on deep reinforcement learning. He is currently a postdoc at UCLouvain. Before that he worked at McGill University/Mila for 2+ years as a postdoc. He did a PhD in machine learning at the university of Liege from which he graduated in September 2017.