14–17 Oct 2019

Kristian Hartikainen
Ph.D. Student, University of Oxford

Kristian Hartikainen is a visiting scholar in the Robotics and AI Lab (RAIL) at UC Berkeley, working with Sergey Levine and Tuomas Haarnoja, and will begin his PhD studies at the University of Oxford with Simon Whiteson in fall 2019. His research focus is on the development of model-free deep reinforcement learning algorithms for robotic control. He’s also working on Ray RLlib, a scalable reinforcement learning library, and Ray Tune, a distributed framework for model training. Kristian is the author and maintainer of Softlearning, the official soft actor-critic project. Previously, he spent several years as a software engineer working on statistical analysis and machine learning products at Statwing and Qualtrics.

Sessions

9:00–12:30 Tuesday, 15 October 2019

Location: Blenheim Room - Palace Suite

Scalable AI and reinforcement learning with Ray

Secondary topics: Machine Learning, Machine Learning tools, Reinforcement Learning

Edward Oakes (UC Berkeley Electrical Engineering & Computer Sciences), Peter Schafhalter (UC Berkeley RISELab), Kristian Hartikainen (University of Oxford)

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Edward Oakes, Peter Schafhalter, and Kristian Hartikainen take a deep dive into Ray, a new distributed execution framework for distributed AI applications developed by machine learning and systems researchers at RISELab, and explore Ray’s API and system architecture and sharing application examples, including several state-of-the-art distributed training, hyperparameter search, and RL algorithms. Read more.