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1711.02827
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Inverse Reward Design
8 November 2017
Dylan Hadfield-Menell
S. Milli
Pieter Abbeel
Stuart J. Russell
Anca Dragan
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Papers citing
"Inverse Reward Design"
50 / 265 papers shown
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Open Questions in Creating Safe Open-ended AI: Tensions Between Control and Creativity
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Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning
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Weakly-Supervised Reinforcement Learning for Controllable Behavior
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242
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Virginia Dignum
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02 Apr 2020
An empirical investigation of the challenges of real-world reinforcement learning
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Nir Levine
D. Mankowitz
Jerry Li
Cosmin Paduraru
Sven Gowal
Todd Hester
OffRL
365
130
0
24 Mar 2020
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
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Benjamin Eysenbach
Xinyang Geng
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Ruslan Salakhutdinov
OffRL
252
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25 Feb 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
International Conference on Machine Learning (ICML), 2020
Daniel S. Brown
Russell Coleman
R. Srinivasan
S. Niekum
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408
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21 Feb 2020
Reward-rational (implicit) choice: A unifying formalism for reward learning
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Hong Jun Jeon
S. Milli
Anca Dragan
354
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12 Feb 2020
Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections
IEEE Transactions on robotics (IEEE Trans. Robot.), 2020
Andreea Bobu
Andrea V. Bajcsy
J. F. Fisac
Sampada Deglurkar
Anca Dragan
169
42
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Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes
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Maxime Bouton
Jana Tumova
Mykel J. Kochenderfer
175
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11 Jan 2020
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
IEEE International Conference on Robotics and Automation (ICRA), 2019
R. Li
Allan Jabri
Trevor Darrell
Pulkit Agrawal
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142
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23 Dec 2019
Relational Mimic for Visual Adversarial Imitation Learning
Lionel Blondé
Yichuan Tang
Jian Zhang
Russ Webb
113
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18 Dec 2019
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning
Riashat Islam
Raihan Seraj
Samin Yeasar Arnob
Doina Precup
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146
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11 Dec 2019
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Neural Information Processing Systems (NeurIPS), 2019
Allan Jabri
Kyle Hsu
Benjamin Eysenbach
Abhishek Gupta
Sergey Levine
Chelsea Finn
VLM
OOD
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165
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09 Dec 2019
Learning Human Objectives by Evaluating Hypothetical Behavior
International Conference on Machine Learning (ICML), 2019
S. Reddy
Anca Dragan
Sergey Levine
Shane Legg
Jan Leike
238
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05 Dec 2019
Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior
Journal of machine learning research (JMLR), 2019
William Hoiles
Vikram Krishnamurthy
Kunal Pattanayak
CML
214
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Reward Tampering Problems and Solutions in Reinforcement Learning: A Causal Influence Diagram Perspective
Tom Everitt
Marcus Hutter
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Victoria Krakovna
418
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13 Aug 2019
Multi-Agent Adversarial Inverse Reinforcement Learning
International Conference on Machine Learning (ICML), 2019
Lantao Yu
Jiaming Song
Stefano Ermon
326
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145
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Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution
Genetic Programming Theory and Practice (GPTP), 2019
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137
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24 Jun 2019
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
International Conference on Machine Learning (ICML), 2019
Rohin Shah
Noah Gundotra
Pieter Abbeel
Anca Dragan
151
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0
23 Jun 2019
Learning Reward Functions by Integrating Human Demonstrations and Preferences
Malayandi Palan
Nicholas C. Landolfi
Gleb Shevchuk
Dorsa Sadigh
142
139
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21 Jun 2019
Planning With Uncertain Specifications (PUnS)
IEEE Robotics and Automation Letters (RA-L), 2019
Ankit J. Shah
Shen Li
J. Shah
186
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07 Jun 2019
Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
Yang Liu
Yunan Luo
Yuanyi Zhong
Xi Chen
Qiang Liu
Jian-wei Peng
182
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31 May 2019
Defining Admissible Rewards for High Confidence Policy Evaluation
ACM Conference on Health, Inference, and Learning (CHIL), 2019
Niranjani Prasad
Barbara E. Engelhardt
Finale Doshi-Velez
OffRL
140
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30 May 2019
Minimizing the Negative Side Effects of Planning with Reduced Models
Sandhya Saisubramanian
S. Zilberstein
71
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22 May 2019
Challenges of Real-World Reinforcement Learning
Gabriel Dulac-Arnold
D. Mankowitz
Todd Hester
OffRL
303
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29 Apr 2019
Energy-Based Continuous Inverse Optimal Control
Yifei Xu
Jianwen Xie
Tianyang Zhao
Chris L. Baker
Yibiao Zhao
Ying Nian Wu
488
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Deep Imitation Learning for Autonomous Driving in Generic Urban Scenarios with Enhanced Safety
IEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2019
Jianyu Chen
Bodi Yuan
Masayoshi Tomizuka
155
147
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02 Mar 2019
Conservative Agency via Attainable Utility Preservation
Alexander Matt Turner
Dylan Hadfield-Menell
Prasad Tadepalli
373
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Parenting: Safe Reinforcement Learning from Human Input
Christopher Frye
Ilya Feige
149
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18 Feb 2019
Preferences Implicit in the State of the World
International Conference on Learning Representations (ICLR), 2019
Rohin Shah
Dmitrii Krasheninnikov
Jordan Alexander
Pieter Abbeel
Anca Dragan
270
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12 Feb 2019
Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications
Thanh Thi Nguyen
Ngoc Duy Nguyen
S. Nahavandi
318
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31 Dec 2018
Estimating Rationally Inattentive Utility Functions with Deep Clustering for Framing - Applications in YouTube Engagement Dynamics
William Hoiles
Vikram Krishnamurthy
72
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Scalable agent alignment via reward modeling: a research direction
Jan Leike
David M. Krueger
Tom Everitt
Miljan Martic
Vishal Maini
Shane Legg
378
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Legible Normativity for AI Alignment: The Value of Silly Rules
Dylan Hadfield-Menell
Mckane Andrus
Gillian K. Hadfield
112
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Deep Reinforcement Learning
Yuxi Li
VLM
OffRL
367
143
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Learning under Misspecified Objective Spaces
Andreea Bobu
Andrea V. Bajcsy
J. F. Fisac
Anca Dragan
293
32
0
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Reinforcement Learning with Perturbed Rewards
Jingkang Wang
Yang Liu
Yue Liu
NoLa
395
151
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Active Inverse Reward Design
Sören Mindermann
Rohin Shah
Adam Gleave
Dylan Hadfield-Menell
261
20
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09 Sep 2018
Multi-Agent Generative Adversarial Imitation Learning
Jiaming Song
Hongyu Ren
Dorsa Sadigh
Stefano Ermon
GAN
203
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Safe Option-Critic: Learning Safety in the Option-Critic Architecture
Arushi Jain
Khimya Khetarpal
Doina Precup
254
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VFunc: a Deep Generative Model for Functions
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Riashat Islam
Alessandro Sordoni
Zafarali Ahmed
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Towards Mixed Optimization for Reinforcement Learning with Program Synthesis
Surya Bhupatiraju
Kumar Krishna Agrawal
Rishabh Singh
137
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Simplifying Reward Design through Divide-and-Conquer
Ellis Ratner
Dylan Hadfield-Menell
Anca Dragan
149
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Including Uncertainty when Learning from Human Corrections
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M. O'Malley
138
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Penalizing side effects using stepwise relative reachability
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Laurent Orseau
Ramana Kumar
Miljan Martic
Shane Legg
287
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04 Jun 2018
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