Sessions

GOTOpia Europe 2020

Reinforcement learning (RL), a sub-discipline of machine learning, has been gaining academic and media notoriety after hyped marketing "reveals" of agents playing various games. But these hide the fact that RL is immensely useful in many practical, industrial situations where hand-coding strategies or policies would be impractical or sub-optimal.

Following the theme of Phil's new book Reinforcement Learning, Phil will present a rebuttal to the hyperbole by analyzing five different industrial case studies from a variety of sectors.

You will learn where RL can be applied, how to spot challenges that fit inside the RL paradigm and what pitfalls to watch out for.

You will learn that RL is more than a bot in a game; it is the next frontier in applied artificial intelligence.

Phil will avoid using jargon to make this talk acceptable for a wider audience, but does expect that you have limited exposure to data science or machine learning in general.

In this talk, you'll learn:

• When you can apply reinforcement learning
• What pitfalls to watch out for when using reinforcement learning
• True-to-life cases form different industries