Mark P. Woodward

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All published works

Action	Title	Year	Authors
+ PDF Chat	Learning to Interactively Learn and Assist	2020	Mark P. Woodward Chelsea Finn Karol Hausman
+	Learning to Interactively Learn and Assist	2019	Mark P. Woodward Chelsea Finn Karol Hausman
+	Training an Interactive Helper	2019	Mark P. Woodward Chelsea Finn Karol Hausman
+	Active One-shot Learning	2017	Mark P. Woodward Chelsea Finn
+	Framing Human-Robot Task Communication as a POMDP	2012	Mark P. Woodward Robert J. Wood
+	Learning from Humans as an I-POMDP	2012	Mark P. Woodward Robert J. Wood

Common Coauthors

Coauthor	Papers Together
Chelsea Finn	4
Karol Hausman	3
Robert J. Wood	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	3
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	3
+	Cooperative Inverse Reinforcement Learning	2016	Dylan Hadfield-Menell Anca D. Dragan Pieter Abbeel Stuart Russell	2
+	Deep Recurrent Q-Learning for Partially Observable MDPs	2015	Matthew Hausknecht Peter Stone	2
+	One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning	2018	Tianhe Yu Chelsea Finn Annie Xie Sudeep Dasari Tianhao Zhang Pieter Abbeel Sergey Levine	2
+	Learning to Communicate with Deep Multi-Agent Reinforcement Learning	2016	Jakob Foerster Yannis Assael Nando de Freitas Shimon Whiteson	2
+	One-shot Learning with Memory-Augmented Neural Networks	2016	Adam Santoro Sergey Bartunov Matthew Botvinick Daan Wierstra Timothy Lillicrap	2
+ PDF Chat	Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces	2018	Garrett Warnell Nicholas R. Waytowich Vernon J. Lawhern Peter Stone	2
+	Task-Embedded Control Networks for Few-Shot Imitation Learning	2018	Stephen James Michael Bloesch Andrew J. Davison	2
+	Observational Learning by Reinforcement Learning	2017	Diana Borsa Bilal Piot Rémi Munos Olivier Pietquin	2
+ PDF Chat	Counterfactual Multi-Agent Policy Gradients	2018	Jakob Foerster Gregory Farquhar Triantafyllos Afouras Nantas Nardelli Shimon Whiteson	1
+	Deep reinforcement learning from human preferences	2017	Paul F. Christiano Jan Leike T. B. Brown Miljan Martic Shane Legg Dario Amodei	1
+	Lenient Multi-Agent Deep Reinforcement Learning	2017	Gregory Palmer Karl Tuyls Daan Bloembergen Rahul Savani	1
+ PDF Chat	Deep Q-learning From Demonstrations	2018	Todd Hester Matej Vecerík Olivier Pietquin Marc Lanctot Tom Schaul Bilal Piot Dan Horgan John Quan Andrew Sendonaris Ian Osband	1
+	Newtonian Action Advice: Integrating Human Verbal Instruction with Reinforcement Learning	2018	Samantha Krening	1
+	Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review	2018	Sergey Levine	1
+	Learning a Prior over Intent via Meta-Inverse Reinforcement Learning	2018	Kelvin Xu Ellis Ratner Anca D. Dragan Sergey Levine Chelsea Finn	1
+	QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation	2018	Dmitry Kalashnikov Alex Irpan Peter Pástor Julian Ibarz Alexander Herzog Eric Jang Deirdre Quillen Ethan Holly Mrinal Kalakrishnan Vincent Vanhoucke	1
+	Active Inverse Reward Design	2018	Sören Mindermann Rohin Shah Adam Gleave Dylan Hadfield-Menell	1
+	Interactive Learning with Corrective Feedback for Policies based on Deep Neural Networks	2018	Rodrigo Pérez‐Dattari Carlos Celemin Javier Ruíz-del-Solar Jens Kober	1
+	HG-DAgger: Interactive Imitation Learning with Human Experts	2018	Michael A. Kelly Chelsea Sidrane Katherine Driggs-Campbell Mykel J. Kochenderfer	1
+	Risk-Aware Active Inverse Reinforcement Learning	2019	Daniel S. Brown Yuchen Cui Scott Niekum	1
+	Deep Reinforcement Learning from Policy-Dependent Human Feedback.	2019	Dilip Arumugam Jun Ki Lee Sophie Saskin Michael L. Littman	1
+	Semi-Supervised Learning with Deep Generative Models	2014	Diederik P. Kingma Danilo Jimenez Rezende Shakir Mohamed Max Welling	1
+	Online Meta-Learning	2019	Chelsea Finn Aravind Rajeswaran Sham M. Kakade Sergey Levine	1
+	Multi-Agent Cooperation and the Emergence of (Natural) Language	2016	Angeliki Lazaridou Alexander Peysakhovich Marco Baroni	1
+	Neural Turing Machines	2014	Alex Graves Greg Wayne Ivo Danihelka	1
+	End-To-End Memory Networks	2015	Sainbayar Sukhbaatar Arthur Szlam Jason Weston Rob Fergus	1
+	Dueling Network Architectures for Deep Reinforcement Learning	2015	Ziyu Wang Tom Schaul Matteo Hessel Hado van Hasselt Marc Lanctot Nando de Freitas	1
+	Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning	2017	Yevgen Chebotar Karol Hausman Marvin Zhang Gaurav S. Sukhatme Stefan Schaal Sergey Levine	1
+	Reward learning from human preferences and demonstrations in Atari	2018	Borja Ibarz Jan Leike Tobias Pohlen Geoffrey Irving Shane Legg Dario Amodei	1
+	A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning	2010	Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell	1
+	Learning a Prior over Intent via Meta-Inverse Reinforcement Learning	2018	Kelvin Xu Ellis Ratner Anca D. Dragan Sergey Levine Chelsea Finn	1
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	1
+	Lenient Multi-Agent Deep Reinforcement Learning	2017	Gregory Palmer Karl Tuyls Daan Bloembergen Rahul Savani	1
+	Newtonian Action Advice: Integrating Human Verbal Instruction with Reinforcement Learning	2018	Samantha Krening Karen M. Feigh	1
+	One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning	2018	Tianhe Yu Chelsea Finn Sudeep Dasari Annie Xie Tianhao Zhang Pieter Abbeel Sergey Levine	1
+	Asynchronous Methods for Deep Reinforcement Learning	2016	Volodymyr Mnih Adrià Puigdomènech Badia Mehdi Mirza Alex Graves Tim Harley Timothy Lillicrap David Silver Koray Kavukcuoglu	1
+ PDF Chat	The Interactions of Rational, Pragmatic Agents Lead to Efficient Language Structure and Use	2020	Benjamin Peloquin Noah D. Goodman Michael C. Frank	1
+ PDF Chat	HG-DAgger: Interactive Imitation Learning with Human Experts	2019	Michael A. Kelly Chelsea Sidrane Katherine Driggs-Campbell Mykel J. Kochenderfer	1
+ PDF Chat	Interactive Learning with Corrective Feedback for Policies Based on Deep Neural Networks	2020	Rodrigo Pérez‐Dattari Carlos Celemin Javier Ruíz-del-Solar Jens Kober	1
+	Deep Reinforcement Learning from Policy-Dependent Human Feedback	2019	Dilip Arumugam Jun Ki Lee Sophie Saskin Michael L. Littman	1
+	Reward learning from human preferences and demonstrations in Atari	2018	Borja Ibarz Jan Leike Tobias Pohlen Geoffrey Irving Shane Legg Dario Amodei	1
+	One-shot Learning with Memory-Augmented Neural Networks	2016	Adam Santoro Sergey Bartunov Matthew Botvinick Daan Wierstra Timothy Lillicrap	1
+	Multi-Agent Cooperation and the Emergence of (Natural) Language	2016	Angeliki Lazaridou Alexander Peysakhovich Marco Baroni	1
+	Playing Atari with Deep Reinforcement Learning	2013	Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller	1
+	Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments	2017	Ryan Lowe Yi Wu Aviv Tamar Jean Harb Pieter Abbeel Igor Mordatch	1
+	Learning to reinforcement learn	2016	Jane X. Wang Zeb Kurth‐Nelson Dhruva Tirumala Hubert Soyer Joel Z. Leibo Rémi Munos Charles Blundell Dharshan Kumaran Matt Botvinick	1
+	Deep reinforcement learning from human preferences	2017	Paul Christiano Jan Leike T. B. Brown Miljan Martic Shane Legg Dario Amodei	1
+	Active Inverse Reward Design	2018	Sören Mindermann Rohin Shah Adam Gleave Dylan Hadfield-Menell	1