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Pieter Abbeel

Pieter Abbeel works in machine learning and robotics, in particular his research focuses on apprenticeship learning (making robots learn from people), reinforcement learning (how to make robots learn through their own trial and error ), and how to speed up skill acquisition through learning-to-learn. His robots have learned advanced helicopter aerobatics, knot-tying, basic assembly, and can organize laundry. His group has pioneered deep reinforcement learning for robotics, including learning visuomotor skills and simulated locomotion.


Best Paper Awards/Finalists, (NIPS 2016, ICRA 2015, ICRA 2013, ICRA 2012, ICRA 2010, ICML 2008) .

Presidential Early Career Award for Scientists and Engineers (PECASE)

IEEE Robotics and Automation Society Early Career Award

Young Investigator Program Awards: ONR, AFOSR, Darpa, NSF

Dick Volz Best U.S. Ph.D. Thesis in Robotics and Automation Award

Relevant Publications

Y. Duan, M. Andrychowicz, B. Stadie, J. Ho, J. Schneider, Il. Sutskever, P. Abbeel, and W. Zaremba, "One-shot Imitation Learning," Neural Information Processing Systems (NIPS), 2017.

J. Tobin, R. Fong, A. Ray, J. Schneider, W. Zaremba, and P. Abbeel, "Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World", in the proceedings of the 30th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, October 2017.

C. Finn, P. Abbeel, and S. Levine, "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks", in the proceedings of the International Conference on Machine Learning (ICML), Sydney, August 2017),.

X. Chen, Y. Duan, R. Houthooft, J. Schulman, I. Sutskever, and P. Abbeel, "InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets," Neural Information Processing Systems (NIPS), 2016.

J. Schulman, S. Levine, P. Moritz, M. I. Jordan, and P. Abbeel, "Trust Region Policy Optimization," In the proceedings of the 32nd International Conference on Machine Learning (ICML), 2015.



Advisor Learning in Machines & Brains


University of California, BerkeleyElectrical Engineering and Computer Sciences


Ph.D. Computer Science Stanford University

M.Sci., Computer Science Stanford University

M.Sci., Electrical Engineering Katholieke Universiteit Leuven

B.Sci, Electrical Engineering Katholieke Universiteit Leuven


United States

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