September 26-27, 2016
New York, NY

Deep reinforcement learning for robotics

Pieter Abbeel (OpenAI / UC Berkeley)
2:20pm–3:00pm Monday, 09/26/2016
Location: River Pavilion B
Average rating: ****.
(4.67, 3 ratings)

Pieter Abbeel explores deep reinforcement learning for robotics.

Photo of Pieter Abbeel

Pieter Abbeel

OpenAI / UC Berkeley

Pieter Abbeel is an associate professor in UC Berkeley’s EECS department, where he works in machine learning and robotics—in particular his research is on making robots learn from people (apprenticeship learning) and how to make robots learn through their own trial and error (reinforcement learning). Pieter’s robots have learned advanced helicopter aerobatics, knot tying, basic assembly, and organizing laundry. He has won various awards, including best paper awards at ICML and ICRA, the Sloan Fellowship, the Air Force Office of Scientific Research Young Investigator Program (AFOSR-YIP) Award, the Office of Naval Research Young Investigator Program (ONR-YIP) Award, the DARPA Young Faculty Award (DARPA-YFA), the National Science Foundation Faculty Early Career Development Program Award (NSF-CAREER), the Presidential Early Career Award for Scientists and Engineers (PECASE), the CRA-E Undergraduate Research Faculty Mentoring Award, the MIT TR35, the IEEE Robotics and Automation Society (RAS) Early Career Award, and the Dick Volz Best US PhD Thesis in Robotics and Automation Award.