Craig
Sherstan

Profile

After a career in software development I returned to the University of Alberta to study artificial intelligence, particularly the field of reinforcement learning. After completing my master’s degree I was awarded the Vanier scholarship, which enabled me to pursue my doctoral degree while raising my two young kids alongside my wife.

My interest in AI is motivated by the desire to create robots that are capable of autonomy in diverse settings and tasks. With this motivation in mind, the primary focus of my doctoral research was on the use of prediction for perception. That is, robots that represent their world and their interactions with it by making predictions about their own sensory experiences.

Message

“At Sony AI I am working with a fantastic team of scientists and engineers doing a mix of pure and applied research in the application of reinforcement learning in video games. I am presently part of a research effort to improve our knowledge of how to practically deploy reinforcement learning algorithms. We are looking for ways to improve the process of agent design.

I feel that the opportunities I have at Sony AI are very unique. I am able to pursue many of my own research interests while staying rooted and motivated by our project oriented goals. I get to learn from the experience of amazing researchers and I also have access to products and technologies that are unique to Sony.”

Publications

Value Function Decomposition for Iterative Design of Reinforcement Learning Agents

NeurIPS, 2022
James MacGlashan, Evan Archer, Alisa Devlic, Takuma Seno, Craig Sherstan, Peter R. Wurman, Peter Stone

Designing reinforcement learning (RL) agents is typically a difficult process that requires numerous design iterations. Learning can fail for a multitude of reasons and standard RL methods provide too few tools to provide insight into the exact cause. In this paper, we show …

Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning

Nature, 2022
Peter Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Kompella, Hao Chih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead Amago, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano

Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical manoeuvres to pass or block…

Blog

July 12, 2022 | Gaming | GT Sophy

How to Train Your Race Car

GT SOPHY TECHNICAL SERIES Starting in 2020, the research and engineering team at Sony AI set out to do something that had never been done before: create an AI agent that could beat the best drivers in the world at the PlayStation®…

GT SOPHY TECHNICAL SERIES Starting in 2020, the research and engineering team at Sony AI set out to do something that had never be…

May 30, 2022 | Sony AI

Meet the Team #5: Craig, Piyush, and Samuel

The fifth installment of our Meet the Team series features members of the global Sony AI team who contributed to the groundbreaking research, Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning, and created th…

The fifth installment of our Meet the Team series features members of the global Sony AI team who contributed to the groundbreakin…

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