Deep Reinforcement Learning: Its basics and practical applications

We have found a new date for Chris to be in good shape and present at our next meetup

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Join us in our first Grenoble Data Science meetup of the 24-25 season.

Chris will discuss reinforcement learning and practical applications.

We address a special thank you to the Cowork In Grenoble and Minimistan teams for their continued support in hosting us.

Looking forward to seeing you!

Abstract
Reinforcement Learning (RL), a key branch of machine learning, focuses on solving decision-making tasks. With the advancement of deep neural networks, RL has become a powerful tool for tackling high-dimensional challenges, such as achieving superhuman performance in Atari games or mastering complex strategic games like chess and Go. Beyond these milestones, RL is increasingly being applied in various practical domains, from industrial control problems to decision-making in economics, marketing, and data science. In this talk, I will introduce the fundamental concepts of RL and provide an overview of its real-world applications.

Short Bio
Chris Reinke is a PostDoc researcher at Inria Grenoble leading the “Learning Robot Behavior” task in a European project about Social Robotics where he investigates Transfer and Meta Reinforcement Learning.
Previously, he worked on automated diversity exploration at Inria Bordeaux and earned his PhD in Reinforcement Learning from the Okinawa Institute of Science and Technology (Japan) in 2018.
He holds a BSc and MSc in Cognitive Science from the University of Osnabrück (Germany) and is a certified Software Developer.