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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 interaction. 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 a high-level view about the current state of the art and potential directions for future contributions.
Fri 6:00 a.m. - 6:30 a.m.
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Talk by Yann Lecunn
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Talk
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Fri 6:30 a.m. - 7:00 a.m.
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Contrbuted Talks
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Talks
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TBD |
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Fri 7:00 a.m. - 7:30 a.m.
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Talk by Jacob Andreas
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Talk
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Fri 7:30 a.m. - 8:00 a.m.
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Coffee
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Fri 8:00 a.m. - 8:30 a.m.
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Talk by Sham Kakade
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Talk
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Fri 9:00 a.m. - 9:30 a.m.
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Talk by Doina Precup
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Talk
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Fri 9:30 a.m. - 10:30 a.m.
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Lunch
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Fri 10:30 a.m. - 11:00 a.m.
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Talk by Satinder Singh
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Talk
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Fri 11:00 a.m. - 11:30 a.m.
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Contributed Talks
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Talks
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Fri 11:30 a.m. - 12:00 p.m.
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Talk by Martha White
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Talk
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Fri 12:00 p.m. - 1:00 p.m.
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Poster Session 1 + Coffee
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Poster session
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Tom Van de Wiele · Rui Zhao · J. Fernando Hernandez-Garcia · Fabio Pardo · Xian Yeow Lee · Xiaolin Andy Li · Marcin Andrychowicz · Jie Tang · Suraj Nair · Juhyeon Lee · Cédric Colas · S. M. Ali Eslami · Yen-Chen Wu · Stephen McAleer · Ryan Julian · Yang Xue · Matthia Sabatelli · Pranav Shyam · Alexandros Kalousis · Giovanni Montana · Emanuele Pesce · Felix Leibfried · Zhanpeng He · Chunxiao Liu · Yanjun Li · Yoshihide Sawada · Alexander Pashevich · Tejas Kulkarni · Keiran Paster · Luca Rigazio · Quan Vuong · Hyunggon Park · Minhae Kwon · Rivindu Weerasekera · Shamane Siriwardhanaa · Rui Wang · Ozsel Kilinc · Keith Ross · Yizhou Wang · Simon Schmitt · Thomas Anthony · Evan Cater · Forest Agostinelli · Tegg Sung · Shirou Maruyama · Alexander Shmakov · Devin Schwab · Mohammad Firouzi · Glen Berseth · Denis Osipychev · Jesse Farebrother · Jianlan Luo · William Agnew · Peter Vrancx · Jonathan Heek · Catalin Ionescu · Haiyan Yin · Megumi Miyashita · Nathan Jay · Noga H. Rotman · Sam Leroux · Shaileshh Bojja Venkatakrishnan · Henri Schmidt · Jack Terwilliger · Ishan Durugkar · Jonathan Sauder · David Kas · Arash Tavakoli · Alain-Sam Cohen · Philip Bontrager · Adam Lerer · Thomas Paine · Ahmed Khalifa · Ruben Rodriguez · Avi Singh · Yiming Zhang
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Fri 1:00 p.m. - 1:30 p.m.
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Talk by Jeff Clune
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Talk
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Fri 1:30 p.m. - 2:15 p.m.
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Contributed Talks
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Talks
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Fri 2:15 p.m. - 3:15 p.m.
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Poster Session 2
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Poster session
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Author Information
Pieter Abbeel (UC Berkeley | Gradescope | 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.
David Silver (DeepMind)
Satinder Singh (University of Michigan)
Joelle Pineau (McGill University)
Joelle Pineau is an Associate Professor and William Dawson Scholar at McGill University where she co-directs the Reasoning and Learning Lab. She also leads the Facebook AI Research lab in Montreal, Canada. She holds a BASc in Engineering from the University of Waterloo, and an MSc and PhD in Robotics from Carnegie Mellon University. Dr. Pineau's research focuses on developing new models and algorithms for planning and learning in complex partially-observable domains. She also works on applying these algorithms to complex problems in robotics, health care, games and conversational agents. She serves on the editorial board of the Journal of Artificial Intelligence Research and the Journal of Machine Learning Research and is currently President of the International Machine Learning Society. She is a recipient of NSERC's E.W.R. Steacie Memorial Fellowship (2018), a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), a Senior Fellow of the Canadian Institute for Advanced Research (CIFAR) and in 2016 was named a member of the College of New Scholars, Artists and Scientists by the Royal Society of Canada.
Joshua Achiam (UC Berkeley, OpenAI)
Rein Houthooft (Happy Elements)
Aravind Srinivas (UC Berkeley)
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Matthia Sabatelli · Adam Stooke · Amir Abdi · Paulo Rauber · Leonard Adolphs · Ian Osband · Hardik Meisheri · Karol Kurach · Johannes Ackermann · Matt Benatan · GUO ZHANG · Chen Tessler · Dinghan Shen · Mikayel Samvelyan · Riashat Islam · Murtaza Dalal · Luke Harries · Andrey Kurenkov · Konrad Żołna · Sudeep Dasari · Kristian Hartikainen · Ofir Nachum · Kimin Lee · Markus Holzleitner · Vu Nguyen · Francis Song · Christopher Grimm · Felipe Leno da Silva · Yuping Luo · Yifan Wu · Alex Lee · Thomas Paine · Wei-Yang Qu · Daniel Graves · Yannis Flet-Berliac · Yunhao Tang · Suraj Nair · Matthew Hausknecht · Akhil Bagaria · Simon Schmitt · Bowen Baker · Paavo Parmas · Benjamin Eysenbach · Lisa Lee · Siyu Lin · Daniel Seita · Abhishek Gupta · Riley Simmons-Edler · Yijie Guo · Kevin Corder · Vikash Kumar · Scott Fujimoto · Adam Lerer · Ignasi Clavera Gilaberte · Nicholas Rhinehart · Ashvin Nair · Ge Yang · Lingxiao Wang · Sungryull Sohn · J. Fernando Hernandez-Garcia · Xian Yeow Lee · Rupesh Srivastava · Khimya Khetarpal · Chenjun Xiao · Luckeciano Carvalho Melo · Rishabh Agarwal · Tianhe Yu · Glen Berseth · Devendra Singh Chaplot · Jie Tang · Anirudh Srinivasan · Tharun Kumar Reddy Medini · Aaron Havens · Misha Laskin · Asier Mujika · Rohan Saphal · Joseph Marino · Alex Ray · Joshua Achiam · Ajay Mandlekar · Zhuang Liu · Danijar Hafner · Zhiwen Tang · Ted Xiao · Michael Walton · Jeff Druce · Ferran Alet · Zhang-Wei Hong · Stephanie Chan · Anusha Nagabandi · Hao Liu · Hao Sun · Ge Liu · Dinesh Jayaraman · John Co-Reyes · Sophia Sanborn -
2019 : Late-Breaking Papers (Talks) »
David Silver · Simon Du · Matthias Plappert -
2019 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Joshua Achiam · Carlos Florensa · Christopher Grimm · Haoran Tang · Vivek Veeriah -
2019 : Pieter Abbeel »
Pieter Abbeel -
2019 Workshop: Retrospectives: A Venue for Self-Reflection in ML Research »
Ryan Lowe · Yoshua Bengio · Joelle Pineau · Michela Paganini · Jessica Forde · Shagun Sodhani · Abhishek Gupta · Joel Lehman · Peter Henderson · Kanika Madan · Koustuv Sinha · Xavier Bouthillier -
2019 Poster: Evaluating Protein Transfer Learning with TAPE »
Roshan Rao · Nicholas Bhattacharya · Neil Thomas · Yan Duan · Peter Chen · John Canny · Pieter Abbeel · Yun Song -
2019 Spotlight: Evaluating Protein Transfer Learning with TAPE »
Roshan Rao · Nicholas Bhattacharya · Neil Thomas · Yan Duan · Peter Chen · John Canny · Pieter Abbeel · Yun Song -
2019 Poster: Goal-conditioned Imitation Learning »
Yiming Ding · Carlos Florensa · Pieter Abbeel · Mariano Phielipp -
2019 Poster: Geometry-Aware Neural Rendering »
Joshua Tobin · Wojciech Zaremba · Pieter Abbeel -
2019 Poster: MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies »
Xue Bin Peng · Michael Chang · Grace Zhang · Pieter Abbeel · Sergey Levine -
2019 Poster: Discovery of Useful Questions as Auxiliary Tasks »
Vivek Veeriah · Matteo Hessel · Zhongwen Xu · Janarthanan Rajendran · Richard L Lewis · Junhyuk Oh · Hado van Hasselt · David Silver · Satinder Singh -
2019 Oral: Geometry-Aware Neural Rendering »
Joshua Tobin · Wojciech Zaremba · Pieter Abbeel -
2019 Poster: No-Press Diplomacy: Modeling Multi-Agent Gameplay »
Philip Paquette · Yuchen Lu · SETON STEVEN BOCCO · Max Smith · Satya O.-G. · Jonathan K. Kummerfeld · Joelle Pineau · Satinder Singh · Aaron Courville -
2019 Poster: Compositional Plan Vectors »
Coline Devin · Daniel Geng · Pieter Abbeel · Trevor Darrell · Sergey Levine -
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 : Pieter Abbeel »
Pieter Abbeel -
2018 : David Silver »
David Silver -
2018 : Joelle Pineau »
Joelle Pineau -
2018 Poster: Temporal Regularization for Markov Decision Process »
Pierre Thodoroff · Audrey Durand · Joelle Pineau · Doina Precup -
2018 Poster: On Learning Intrinsic Rewards for Policy Gradient Methods »
Zeyu Zheng · Junhyuk Oh · Satinder Singh -
2018 Poster: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
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Thanard Kurutach · Aviv Tamar · Ge Yang · Stuart Russell · Pieter Abbeel -
2018 Spotlight: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Invited Talk: Reproducible, Reusable, and Robust Reinforcement Learning »
Joelle Pineau -
2018 Poster: Completing State Representations using Spectral Learning »
Nan Jiang · Alex Kulesza · Satinder Singh -
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Rein Houthooft · Yuhua Chen · Phillip Isola · Bradly Stadie · Filip Wolski · OpenAI Jonathan Ho · Pieter Abbeel -
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Brian Skyrms · Satinder Singh · Jacob Andreas -
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Matt Botvinick · Emma Brunskill · Marcos Campos · Jan Peters · Doina Precup · David Silver · Josh Tenenbaum · Roy Fox -
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Satinder Singh -
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Pieter Abbeel -
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Satinder Singh -
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Pieter Abbeel · Gregory Kahn -
2017 : Deep Reinforcement Learning with Subgoals (David Silver) »
David Silver -
2017 : Invited Talk - Joelle Pineau »
Joelle Pineau -
2017 : Invited Talk - Satindar Singh »
Satinder Singh -
2017 Symposium: Deep Reinforcement Learning »
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2017 Poster: Repeated Inverse Reinforcement Learning »
Kareem Amin · Nan Jiang · Satinder Singh -
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2017 Poster: #Exploration: A Study of Count-Based Exploration for Deep Reinforcement Learning »
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2017 Poster: Successor Features for Transfer in Reinforcement Learning »
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2017 Poster: A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning »
Marc Lanctot · Vinicius Zambaldi · Audrunas Gruslys · Angeliki Lazaridou · Karl Tuyls · Julien Perolat · David Silver · Thore Graepel -
2017 Poster: Imagination-Augmented Agents for Deep Reinforcement Learning »
Sébastien Racanière · Theophane Weber · David Reichert · Lars Buesing · Arthur Guez · Danilo Jimenez Rezende · Adrià Puigdomènech Badia · Oriol Vinyals · Nicolas Heess · Yujia Li · Razvan Pascanu · Peter Battaglia · Demis Hassabis · David Silver · Daan Wierstra -
2017 Poster: Inverse Reward Design »
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan -
2017 Spotlight: Successor Features for Transfer in Reinforcement Learning »
Andre Barreto · Will Dabney · Remi Munos · Jonathan Hunt · Tom Schaul · David Silver · Hado van Hasselt -
2017 Spotlight: Natural Value Approximators: Learning when to Trust Past Estimates »
Zhongwen Xu · Joseph Modayil · Hado van Hasselt · Andre Barreto · David Silver · Tom Schaul -
2017 Spotlight: Repeated Inverse Reinforcement Learning »
Kareem Amin · Nan Jiang · Satinder Singh -
2017 Oral: Inverse Reward Design »
Dylan Hadfield-Menell · Smitha Milli · Pieter Abbeel · Stuart J Russell · Anca Dragan -
2017 Oral: Imagination-Augmented Agents for Deep Reinforcement Learning »
Sébastien Racanière · Theophane Weber · David Reichert · Lars Buesing · Arthur Guez · Danilo Jimenez Rezende · Adrià Puigdomènech Badia · Oriol Vinyals · Nicolas Heess · Yujia Li · Razvan Pascanu · Peter Battaglia · Demis Hassabis · David Silver · Daan Wierstra -
2017 Invited Talk: Deep Learning for Robotics »
Pieter Abbeel -
2017 Demonstration: A Deep Reinforcement Learning Chatbot »
Iulian Vlad Serban · Chinnadhurai Sankar · Mathieu Germain · Saizheng Zhang · Zhouhan Lin · Sandeep Subramanian · Taesup Kim · Michael Pieper · Sarath Chandar · Nan Rosemary Ke · Sai Rajeswar Mudumba · Alexandre de Brébisson · Jose Sotelo · Dendi A Suhubdy · Vincent Michalski · Joelle Pineau · Yoshua Bengio -
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 -
2017 Poster: Multitask Spectral Learning of Weighted Automata »
Guillaume Rabusseau · Borja Balle · Joelle Pineau -
2017 Poster: Value Prediction Network »
Junhyuk Oh · Satinder Singh · Honglak Lee -
2016 : Joelle Pineau »
Joelle Pineau -
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: Learning values across many orders of magnitude »
Hado van Hasselt · Arthur Guez · Arthur Guez · Matteo Hessel · Volodymyr Mnih · David Silver -
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 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 Tutorial: Deep Reinforcement Learning Through Policy Optimization »
Pieter Abbeel · John Schulman -
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 -
2015 Poster: Action-Conditional Video Prediction using Deep Networks in Atari Games »
Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh -
2015 Spotlight: Action-Conditional Video Prediction using Deep Networks in Atari Games »
Junhyuk Oh · Xiaoxiao Guo · Honglak Lee · Richard L Lewis · Satinder Singh -
2015 Poster: Learning Continuous Control Policies by Stochastic Value Gradients »
Nicolas Heess · Gregory Wayne · David Silver · Timothy Lillicrap · Tom Erez · Yuval Tassa -
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 Workshop: From Bad Models to Good Policies (Sequential Decision Making under Uncertainty) »
Odalric-Ambrym Maillard · Timothy A Mann · Shie Mannor · Jeremie Mary · Laurent Orseau · Thomas Dietterich · Ronald Ortner · Peter Grünwald · Joelle Pineau · Raphael Fonteneau · Georgios Theocharous · Esteban D Arcaute · Christos Dimitrakakis · Nan Jiang · Doina Precup · Pierre-Luc Bacon · Marek Petrik · Aviv Tamar -
2014 Workshop: Autonomously Learning Robots »
Gerhard Neumann · Joelle Pineau · Peter Auer · Marc Toussaint -
2014 Poster: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2014 Demonstration: SmartWheeler – A smart robotic wheelchair platform »
Martin Gerdzhev · Joelle Pineau · Angus Leigh · Andrew Sutcliffe -
2014 Spotlight: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2014 Poster: Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning »
Xiaoxiao Guo · Satinder Singh · Honglak Lee · Richard L Lewis · Xiaoshi Wang -
2013 Poster: Reward Mapping for Transfer in Long-Lived Agents »
Xiaoxiao Guo · Satinder Singh · Richard L Lewis -
2013 Poster: Learning from Limited Demonstrations »
Beomjoon Kim · Amir-massoud Farahmand · Joelle Pineau · Doina Precup -
2013 Poster: Bellman Error Based Feature Generation using Random Projections on Sparse Spaces »
Mahdi Milani Fard · Yuri Grinberg · Amir-massoud Farahmand · Joelle Pineau · Doina Precup -
2013 Spotlight: Learning from Limited Demonstrations »
Beomjoon Kim · Amir-massoud Farahmand · Joelle Pineau · Doina Precup -
2013 Session: Oral Session 9 »
Satinder Singh -
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 -
2012 Poster: On-line Reinforcement Learning Using Incremental Kernel-Based Stochastic Factorization »
Andre S Barreto · Doina Precup · Joelle Pineau -
2011 Session: Oral Session 10 »
Joelle Pineau -
2011 Poster: Reinforcement Learning using Kernel-Based Stochastic Factorization »
Andre S Barreto · Doina Precup · Joelle Pineau -
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 -
2010 Poster: PAC-Bayesian Model Selection for Reinforcement Learning »
Mahdi Milani Fard · Joelle Pineau -
2010 Poster: Reward Design via Online Gradient Ascent »
Jonathan D Sorg · Satinder Singh · Richard L Lewis -
2009 Poster: Manifold Embeddings for Model-Based Reinforcement Learning under Partial Observability »
Keith Bush · Joelle Pineau -
2008 Poster: Simple Local Models for Complex Dynamical Systems »
Erik Talvitie · Satinder Singh -
2008 Oral: Simple Local Models for Complex Dynamical Systems »
Erik Talvitie · Satinder Singh -
2008 Poster: MDPs with Non-Deterministic Policies »
Mahdi Milani Fard · Joelle Pineau -
2007 Oral: Exponential Family Predictive Representations of State »
David Wingate · Satinder Singh -
2007 Poster: Exponential Family Predictive Representations of State »
David Wingate · Satinder Singh -
2007 Spotlight: Bayes-Adaptive POMDPs »
Stephane Ross · Brahim Chaib-draa · Joelle Pineau -
2007 Spotlight: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2007 Poster: Bayes-Adaptive POMDPs »
Stephane Ross · Brahim Chaib-draa · Joelle Pineau -
2007 Poster: Hierarchical Apprenticeship Learning with Application to Quadruped Locomotion »
J. Zico Kolter · Pieter Abbeel · Andrew Y Ng -
2007 Poster: Theoretical Analysis of Heuristic Search Methods for Online POMDPs »
Stephane Ross · Joelle Pineau · Brahim Chaib-draa -
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