ML Infra + Apps

Large-scale deep learning to augment production RL workloads

Wednesday, August 24
1:15 PM - 1:45 PM

At Riot Games, we leverage large-scale deep reinforcement learning to build bots that play our games at various skill levels to provide additional signals to our designers and ensure that we are releasing the best experiences for our players. As part of this experience we've experimented with multiple methods for controlling and tuning game servers to get the most out of our training time while the bots are learning to play the game. With our game Team Fight Tactics, we were able to take a unique approach that leveraged large neural networks to predict outcomes rather than have to rely on the server. In this talk, we will discuss the supervised learning process that we took and how we simplified and scaled with Ray Data, Ray Train, and Ray Tune.

About Wesley

Wesley Kerr is an experienced data scientist with a demonstrated history of working in tech and gaming. He is a strong engineering professional with a PhD focused on ML/AI with a minor in cognitive science from the University of Arizona.

Wesley Kerr

Head of Tech Research, Riot Games
chucks
Ray Summit 2022 horizontal logo

Ready to Register?

Come connect with the global community of thinkers and disruptors who are building and deploying the next generation of AI and ML applications.

Save your spot
register-bottom-mobile
beanbags

Join the Conversation

Ready to get involved in the Ray community before the conference? Ask a question in the forums. Open a pull request. Or share why you’re excited with the hashtag #RaySummit on Twitter.