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Deep Reinforcement Learning
Pieter Abbeel · Chelsea Finn · David Silver · Matthew Taylor · Martha White · Srijita Das · Yuqing Du · Andrew Patterson · Manan Tomar · Olivia Watkins

Mon Dec 13 08:55 AM -- 06:00 PM (PST) @
Event URL: https://sites.google.com/view/deep-rl-workshop-neurips2021 »

In recent years, the use of deep neural networks as function approximators has enabled researchers to extend reinforcement learning techniques to solve increasingly complex control tasks. The emerging field of deep reinforcement learning has led to remarkable empirical results in rich and varied domains like robotics, strategy games, and multiagent interactions. This workshop will bring together researchers working at the intersection of deep learning and reinforcement learning, and it will help interested researchers outside of the field gain perspective about the current state of the art and potential directions for future contributions.

Author Information

Pieter Abbeel (UC Berkeley & Covariant)

Pieter Abbeel is Professor and Director of the Robot Learning Lab at UC Berkeley [2008- ], Co-Director of the Berkeley AI Research (BAIR) Lab, Co-Founder of covariant.ai [2017- ], Co-Founder of Gradescope [2014- ], Advisor to OpenAI, Founding Faculty Partner AI@TheHouse venture fund, Advisor to many AI/Robotics start-ups. He works in machine learning and robotics. In particular his research focuses on making robots learn from people (apprenticeship learning), how to make robots learn through their own trial and error (reinforcement learning), and how to speed up skill acquisition through learning-to-learn (meta-learning). His robots have learned advanced helicopter aerobatics, knot-tying, basic assembly, organizing laundry, locomotion, and vision-based robotic manipulation. He has won numerous awards, including best paper awards at ICML, NIPS and ICRA, early career awards from NSF, Darpa, ONR, AFOSR, Sloan, TR35, IEEE, and the Presidential Early Career Award for Scientists and Engineers (PECASE). Pieter's work is frequently featured in the popular press, including New York Times, BBC, Bloomberg, Wall Street Journal, Wired, Forbes, Tech Review, NPR.

Chelsea Finn (Stanford)
David Silver (DeepMind)
Matthew Taylor (U. of Alberta)
Martha White (University of Alberta)
Srijita Das (University of Alberta)
Yuqing Du (UC Berkeley)
Andrew Patterson (University of Alberta)
Manan Tomar (University of Alberta)
Olivia Watkins (UC Berkeley)

I'm currently exploring several areas of machine learning, including reinforcement learning, computer vision, and their applications to robotics.

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