Inverse Reward Design

8 November 2017

Dylan Hadfield-Menell

Pieter Abbeel

Papers citing "Inverse Reward Design"

49 / 99 papers shown

Title
Reactive and Safe Road User Simulations using Neural Barrier Certificates Yue Meng Zengyi Qin Chuchu Fan 40 20 0 14 Sep 2021
Hindsight Reward Tweaking via Conditional Deep Reinforcement Learning Ning Wei Jiahua Liang Di Xie Shiliang Pu 25 0 0 06 Sep 2021
Balancing Performance and Human Autonomy with Implicit Guidance Agent Ryo Nakahashi Seiji Yamada 27 4 0 01 Sep 2021
A Hybrid Rule-Based and Data-Driven Approach to Driver Modeling through Particle Filtering Raunak P. Bhattacharyya Soyeon Jung Liam A. Kruse Ransalu Senanayake Mykel Kochenderfer 18 26 0 29 Aug 2021
Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback Xiaofei Wang Kimin Lee Kourosh Hakhamaneshi Pieter Abbeel Michael Laskin 34 42 0 11 Aug 2021
Risk Averse Bayesian Reward Learning for Autonomous Navigation from Human Demonstration Christian Ellis Maggie B. Wigness J. Rogers Craig T. Lennon L. Fiondella 90 6 0 31 Jul 2021
Offline Meta-Reinforcement Learning with Online Self-Supervision Vitchyr H. Pong Ashvin Nair Laura M. Smith Catherine Huang Sergey Levine OffRL 36 66 0 08 Jul 2021
Supervised Bayesian Specification Inference from Demonstrations Ankit J. Shah Pritish Kamath Shen Li Patrick L. Craven Kevin J. Landers Kevin B. Oden J. Shah 27 3 0 06 Jul 2021
The MineRL BASALT Competition on Learning from Human Feedback Rohin Shah Cody Wild Steven H. Wang Neel Alex Brandon Houghton ... Stephanie Milani Nicholay Topin Pieter Abbeel Stuart J. Russell Anca Dragan 41 31 0 05 Jul 2021
Unsupervised Skill Discovery with Bottleneck Option Learning Jaekyeom Kim Seohong Park Gunhee Kim 32 32 0 27 Jun 2021
Hard Choices in Artificial Intelligence Roel Dobbe T. Gilbert Yonatan Dov Mintz 29 52 0 10 Jun 2021
Goal Misgeneralization in Deep Reinforcement Learning L. Langosco Jack Koch Lee D. Sharkey J. Pfau Laurent Orseau David M. Krueger 30 78 0 28 May 2021
A Survey on Interactive Reinforcement Learning: Design Principles and Open Challenges Christian Arzate Cruz Takeo Igarashi OffRL 17 94 0 27 May 2021
Understanding and Avoiding AI Failures: A Practical Guide R. M. Williams Roman V. Yampolskiy 35 24 0 22 Apr 2021
Maximum Entropy RL (Provably) Solves Some Robust RL Problems Benjamin Eysenbach Sergey Levine OOD 50 176 0 10 Mar 2021
Self-Supervised Online Reward Shaping in Sparse-Reward Environments F. Memarian Wonjoon Goo Rudolf Lioutikov S. Niekum Ufuk Topcu OffRL 36 48 0 08 Mar 2021
Multi-Principal Assistance Games: Definition and Collegial Mechanisms Arnaud Fickinger Simon Zhuang Andrew Critch Dylan Hadfield-Menell Stuart J. Russell 19 4 0 29 Dec 2020
Avoiding Tampering Incentives in Deep RL via Decoupled Approval J. Uesato Ramana Kumar Victoria Krakovna Tom Everitt Richard Ngo Shane Legg 28 14 0 17 Nov 2020
REALab: An Embedded Perspective on Tampering Ramana Kumar J. Uesato Richard Ngo Tom Everitt Victoria Krakovna Shane Legg 30 10 0 17 Nov 2020
Learning Dense Rewards for Contact-Rich Manipulation Tasks Zheng Wu Wenzhao Lian Vaibhav Unhelkar Masayoshi Tomizuka S. Schaal 8 37 0 17 Nov 2020
Reward Machines: Exploiting Reward Function Structure in Reinforcement Learning Rodrigo Toro Icarte Toryn Q. Klassen Richard Valenzano Sheila A. McIlraith OffRL 46 216 0 06 Oct 2020
Hidden Incentives for Auto-Induced Distributional Shift David M. Krueger Tegan Maharaj Jan Leike 13 49 0 19 Sep 2020
Avoiding Negative Side Effects due to Incomplete Knowledge of AI Systems Sandhya Saisubramanian S. Zilberstein Ece Kamar 20 21 0 24 Aug 2020
Bayesian Robust Optimization for Imitation Learning Daniel S. Brown S. Niekum Marek Petrik 32 32 0 24 Jul 2020
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate Mirco Mutti Lorenzo Pratissoli Marcello Restelli 11 19 0 09 Jul 2020
Avoiding Side Effects in Complex Environments Alexander Matt Turner Neale Ratzlaff Prasad Tadepalli 30 34 0 11 Jun 2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior Lisa Lee Benjamin Eysenbach Ruslan Salakhutdinov S. Gu Chelsea Finn SSL 22 26 0 06 Apr 2020
An empirical investigation of the challenges of real-world reinforcement learning Gabriel Dulac-Arnold Nir Levine D. Mankowitz Jerry Li Cosmin Paduraru Sven Gowal Todd Hester OffRL 34 121 0 24 Mar 2020
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach Xinyang Geng Sergey Levine Ruslan Salakhutdinov OffRL 18 86 0 25 Feb 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences Daniel S. Brown Russell Coleman R. Srinivasan S. Niekum BDL 35 101 0 21 Feb 2020
Reward-rational (implicit) choice: A unifying formalism for reward learning Hong Jun Jeon S. Milli Anca Dragan 17 176 0 12 Feb 2020
Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections Andreea Bobu Andrea V. Bajcsy J. F. Fisac Sampada Deglurkar Anca Dragan 30 41 0 03 Feb 2020
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes Maxime Bouton Jana Tumova Mykel J. Kochenderfer 14 26 0 11 Jan 2020
Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior William Hoiles Vikram Krishnamurthy Kunal Pattanayak CML 35 25 0 24 Oct 2019
Planning With Uncertain Specifications (PUnS) Ankit J. Shah Shen Li J. Shah 24 25 0 07 Jun 2019
Conservative Agency via Attainable Utility Preservation Alexander Matt Turner Dylan Hadfield-Menell Prasad Tadepalli 30 49 0 26 Feb 2019
Deep Reinforcement Learning for Multi-Agent Systems: A Review of Challenges, Solutions and Applications Thanh Thi Nguyen Ngoc Duy Nguyen S. Nahavandi 27 775 0 31 Dec 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 397 0 19 Nov 2018
Learning under Misspecified Objective Spaces Andreea Bobu Andrea V. Bajcsy J. F. Fisac Anca Dragan 19 30 0 11 Oct 2018
Multi-Agent Generative Adversarial Imitation Learning Jiaming Song Hongyu Ren Dorsa Sadigh Stefano Ermon GAN 27 216 0 26 Jul 2018
Safe Option-Critic: Learning Safety in the Option-Critic Architecture Arushi Jain Khimya Khetarpal Doina Precup 21 26 0 21 Jul 2018
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition Justin Fu Avi Singh Dibya Ghosh Larry Yang Sergey Levine BDL 14 125 0 29 May 2018
Playing hard exploration games by watching YouTube Y. Aytar Tobias Pfaff David Budden T. Paine Ziyun Wang Nando de Freitas 35 269 0 29 May 2018
Reward Estimation for Variance Reduction in Deep Reinforcement Learning Joshua Romoff Peter Henderson Alexandre Piché Vincent François-Lavet Joelle Pineau 11 42 0 09 May 2018
AGI Safety Literature Review Tom Everitt G. Lea Marcus Hutter AI4CE 36 115 0 03 May 2018
Modeling Others using Oneself in Multi-Agent Reinforcement Learning Roberta Raileanu Emily L. Denton Arthur Szlam Rob Fergus 28 199 0 26 Feb 2018
Counterfactual equivalence for POMDPs, and underlying deterministic environments Stuart Armstrong 18 2 0 11 Jan 2018
AI Safety Gridworlds Jan Leike Miljan Martic Victoria Krakovna Pedro A. Ortega Tom Everitt Andrew Lefrancq Laurent Orseau Shane Legg 44 250 0 27 Nov 2017
Deep Reinforcement Learning: An Overview Yuxi Li OffRL VLM 104 1,505 0 25 Jan 2017