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Author Information
Pierre-Yves Oudeyer (INRIA)
Marc Bellemare (Google Brain)
Peter Stone (The University of Texas at Austin)
Matt Botvinick (Google DeepMind / University College London)
Susan Murphy (Harvard University)
Anusha Nagabandi (UC Berkeley)
Ashley Edwards (DeepMind)
Karen Liu (Stanford University)
Pieter Abbeel (UC Berkeley & covariant.ai)
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.
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2019 Poster: On the Utility of Learning about Humans for Human-AI Coordination »
Micah Carroll · Rohin Shah · Mark Ho · Tom Griffiths · Sanjit Seshia · Pieter Abbeel · Anca Dragan -
2019 Poster: Compression with Flows via Local Bits-Back Coding »
Jonathan Ho · Evan Lohn · Pieter Abbeel -
2019 Poster: Guided Meta-Policy Search »
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2019 Spotlight: Compression with Flows via Local Bits-Back Coding »
Jonathan Ho · Evan Lohn · Pieter Abbeel -
2019 Spotlight: Guided Meta-Policy Search »
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2018 : Peter Stone »
Peter Stone -
2018 : Control Algorithms for Imitation Learning from Observation »
Peter Stone -
2018 : Pieter Abbeel »
Pieter Abbeel -
2018 : Learning to Adapt in Dynamic, Real-World Environments via Meta-Reinforcement Learning »
Anusha Nagabandi -
2018 : Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL »
Anusha Nagabandi -
2018 : Peter Stone »
Peter Stone -
2018 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · David Silver · Satinder Singh · Joelle Pineau · Joshua Achiam · Rein Houthooft · Aravind Srinivas -
2018 Poster: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Poster: Learning Plannable Representations with Causal InfoGAN »
Thanard Kurutach · Aviv Tamar · Ge Yang · Stuart Russell · Pieter Abbeel -
2018 Poster: Learning to Share and Hide Intentions using Information Regularization »
DJ Strouse · Max Kleiman-Weiner · Josh Tenenbaum · Matt Botvinick · David Schwab -
2018 Spotlight: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Poster: Evolved Policy Gradients »
Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel -
2018 Spotlight: Evolved Policy Gradients »
Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel -
2018 Poster: The Importance of Sampling inMeta-Reinforcement Learning »
Bradly Stadie · Ge Yang · Rein Houthooft · Peter Chen · Yan Duan · Yuhuai Wu · Pieter Abbeel · Ilya Sutskever -
2017 : Panel Discussion »
Matt Botvinick · Emma Brunskill · Marcos Campos · Jan Peters · Doina Precup · David Silver · Josh Tenenbaum · Roy Fox -
2017 : Applying variational information bottleneck in hierarchical domains (Matt Botvinick) »
Matt Botvinick -
2017 : Meta-reinforcement learning in brains and machines »
Matt Botvinick -
2017 : Meta-Learning Shared Hierarchies (Pieter Abbeel) »
Pieter Abbeel -
2017 : Exhausting the Sim with Domain Randomization and Trying to Exhaust the Real World, Pieter Abbeel, UC Berkeley and Embodied Intelligence »
Pieter Abbeel · Gregory Kahn -
2017 : Keynote: Susan Murphy, U. Michigan »
Susan Murphy -
2017 Symposium: Deep Reinforcement Learning »
Pieter Abbeel · Yan Duan · David Silver · Satinder Singh · Junhyuk Oh · Rein Houthooft -
2017 Poster: #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning »
Haoran Tang · Rein Houthooft · Davis Foote · Adam Stooke · OpenAI Xi Chen · Yan Duan · John Schulman · Filip DeTurck · Pieter Abbeel -
2017 Poster: Action Centered Contextual Bandits »
Kristjan Greenewald · Ambuj Tewari · Susan Murphy · Predag Klasnja -
2017 Poster: Inverse Reward Design »
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan -
2017 Oral: Inverse Reward Design »
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan -
2017 Invited Talk: Deep Learning for Robotics »
Pieter Abbeel -
2017 Demonstration: Deep Robotic Learning using Visual Imagination and Meta-Learning »
Chelsea Finn · Frederik Ebert · Tianhe Yu · Annie Xie · Sudeep Dasari · Pieter Abbeel · Sergey Levine -
2017 Poster: One-Shot Imitation Learning »
Yan Duan · Marcin Andrychowicz · Bradly Stadie · OpenAI Jonathan Ho · Jonas Schneider · Ilya Sutskever · Pieter Abbeel · Wojciech Zaremba -
2016 : Peter Stone (University of Texas at Austin) »
Peter Stone -
2016 : Pieter Abbeel (University of California, Berkeley) »
Pieter Abbeel -
2016 : Invited Talk: Safe Reinforcement Learning for Robotics (Pieter Abbeel, UC Berkeley and OpenAI) »
Pieter Abbeel -
2016 Workshop: Deep Reinforcement Learning »
David Silver · Satinder Singh · Pieter Abbeel · Peter Chen -
2016 Poster: Unifying Count-Based Exploration and Intrinsic Motivation »
Marc Bellemare · Sriram Srinivasan · Georg Ostrovski · Tom Schaul · David Saxton · Remi Munos -
2016 Poster: Backprop KF: Learning Discriminative Deterministic State Estimators »
Tuomas Haarnoja · Anurag Ajay · Sergey Levine · Pieter Abbeel -
2016 Poster: Learning to Poke by Poking: Experiential Learning of Intuitive Physics »
Pulkit Agrawal · Ashvin Nair · Pieter Abbeel · Jitendra Malik · Sergey Levine -
2016 Oral: Learning to Poke by Poking: Experiential Learning of Intuitive Physics »
Pulkit Agrawal · Ashvin Nair · Pieter Abbeel · Jitendra Malik · Sergey Levine -
2016 Demonstration: Autonomous exploration, active learning and human guidance with open-source Poppy humanoid robot platform and Explauto library »
Sébastien Forestier · Yoan Mollard · Pierre-Yves Oudeyer -
2016 Poster: Combinatorial Energy Learning for Image Segmentation »
Jeremy Maitin-Shepard · Viren Jain · Michal Januszewski · Peter Li · Pieter Abbeel -
2016 Poster: InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets »
Xi Chen · Peter Chen · Yan Duan · Rein Houthooft · John Schulman · Ilya Sutskever · Pieter Abbeel -
2016 Poster: VIME: Variational Information Maximizing Exploration »
Rein Houthooft · Xi Chen · Peter Chen · Yan Duan · John Schulman · Filip De Turck · Pieter Abbeel -
2016 Poster: Value Iteration Networks »
Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas -
2016 Oral: Value Iteration Networks »
Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas -
2016 Poster: Cooperative Inverse Reinforcement Learning »
Dylan Hadfield-Menell · Stuart J Russell · Pieter Abbeel · Anca Dragan -
2016 Poster: Safe and Efficient Off-Policy Reinforcement Learning »
Remi Munos · Tom Stepleton · Anna Harutyunyan · Marc Bellemare -
2016 Tutorial: Deep Reinforcement Learning Through Policy Optimization »
Pieter Abbeel · John Schulman -
2015 Workshop: Learning, Inference and Control of Multi-Agent Systems »
Vicenç Gómez · Gerhard Neumann · Jonathan S Yedidia · Peter Stone -
2015 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · John Schulman · Satinder Singh · David Silver -
2015 Poster: Gradient Estimation Using Stochastic Computation Graphs »
John Schulman · Nicolas Heess · Theophane Weber · Pieter Abbeel -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Poster: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2014 Spotlight: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2012 Poster: Exploration in Model-based Reinforcement Learning by Empirically Estimating Learning Progress »
Manuel Lopes · Tobias Lang · Marc Toussaint · Pierre-Yves Oudeyer -
2012 Poster: Near Optimal Chernoff Bounds for Markov Decision Processes »
Teodor Mihai Moldovan · Pieter Abbeel -
2012 Spotlight: Near Optimal Chernoff Bounds for Markov Decision Processes »
Teodor Mihai Moldovan · Pieter Abbeel -
2010 Workshop: Learning and Planning from Batch Time Series Data »
Daniel Lizotte · Michael Bowling · Susan Murphy · Joelle Pineau · Sandeep Vijan -
2010 Spotlight: On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient »
Jie Tang · Pieter Abbeel -
2010 Poster: On a Connection between Importance Sampling and the Likelihood Ratio Policy Gradient »
Jie Tang · Pieter Abbeel -
2007 Spotlight: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2007 Poster: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2006 Poster: Max-margin classification of incomplete data »
Gal Chechik · Geremy Heitz · Gal Elidan · Pieter Abbeel · Daphne Koller -
2006 Spotlight: Max-margin classification of incomplete data »
Gal Chechik · Geremy Heitz · Gal Elidan · Pieter Abbeel · Daphne Koller -
2006 Poster: An Application of Reinforcement Learning to Aerobatic Helicopter Flight »
Pieter Abbeel · Adam P Coates · Andrew Y Ng · Morgan Quigley -
2006 Talk: An Application of Reinforcement Learning to Aerobatic Helicopter Flight »
Pieter Abbeel · Adam P Coates · Andrew Y Ng · Morgan Quigley