Varun
Kompella

Profile

Varun is currently a research scientist at Sony AI. He earned his master’s of science degree in informatics with a specialization in graphics, vision and robotics from Institut Nationale Polytechnique de Grenoble (INRIA Grenoble), and a Ph.D degree from Università della Svizzera Italiana (IDSIA Lugano), Switzerland, working with Prof. Juergen Schmidhuber. In his thesis work he developed algorithms that use the slowness principle for driving exploration in reinforcement learning agents. After completing his Ph.D., he worked as a postdoctoral researcher at the Institute for Neural Computation (INI), Germany. His research contributions led to several patents, publications in peer-reviewed journals and conference proceedings.

Message

“My current focus at Sony AI is to develop algorithms to speed up learning multiple off-policy reinforcement learning tasks.”

Publications

Event Tables for Efficient Experience Replay

CoLLAs, 2023
Varun Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone

Experience replay (ER) is a crucial component of many deep reinforcement learning (RL) systems. However, uniform sampling from an ER buffer can lead to slow convergence and unstable asymptotic behaviors. This paper introduces Stratified Sampling from Event Tables (SSET), whi…

Event Tables for Efficient Experience Replay

TMLR, 2023
Varun Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone

Experience replay (ER) is a crucial component of many deep reinforcement learning (RL) systems. However, uniform sampling from an ER buffer can lead to slow convergence and unstable asymptotic behaviors. This paper introduces Stratified Sampling from Event Tables (SSET), whi…

Outracing Champion Gran Turismo Drivers with Deep Reinforcement Learning

Nature, 2022
Pete 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…

March 3, 2021 | Life at Sony AI

The Challenge to Create a Pandemic Simulator

The thing I like most about working at Sony AI is the quality of the projects we're working on, both for their scientific challenges and for their potential for improving the world. What could be more exciting than magnifying hu…

The thing I like most about working at Sony AI is the quality of the projects we're working on, both for their scientific challen…

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