James Bergstra — accepted AI-conference papers

2018

Benchmarking Reinforcement Learning Algorithms on Real-World Robots

A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra

CoRL 2018

Through many recent successes in simulation, model-free reinforcement learning has emerged as a promising approach to solving continuous control robotic tasks. The research community is now able to reproduce, analyze and build quickly on these results due to open source implementations of learning a

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2018

Setting up a Reinforcement Learning Task with a Real-World Robot

A. Rupam Mahmood, Dmytro Korenkevych, Brent J. Komer, James Bergstra

IROS 2018poster

Reinforcement learning is a promising approach to developing hard-to-engineer adaptive solutions for complex and diverse robotic tasks. However, learning with real-world robots is often unreliable and difficult, which resulted in their low adoption in reinforcement learning research. This difficulty…

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