The 2017 Ben Taskar Memorial Lecture will take place on 2/2/2017, supported jointly with the UW CSE Distinguished Lecturer series.
The Distinguished Lecture will be delivered by Pieter Abbeel, Associate Professor, UC Berkeley, EECS, and Co-Founder of Gradescope. Please see abstract below.
Prior to the lecture, the Taskar Center for Accessible Technology will hold a luncheon on accessible work and play environments, in conjunction with our participation in the exhibit
"Open to All"
Please indicate which events you wish to attend on our submission form at the bottom of this page.
Deep Reinforcement Learning for Robotics
Deep learning has enabled significant advances in supervised learning problems such as speech recognition and visual recognition. Reinforcement learning provides only a weaker supervisory signal, posing additional challenges in the form of temporal credit assignment and exploration. Nevertheless, deep reinforcement learning has already enabled learning to play Atari games from raw pixels (without access to the underlying game state) and learning certain types of visuomotor manipulation primitives. I will discuss major challenges for, as well as some preliminary promising results towards, making deep reinforcement learning applicable to real robotic problems.
Pieter Abbeel (Associate Professor, UC Berkeley EECS) 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). His 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 U.S. Ph.D. Thesis in Robotics and Automation Award.