Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation

26 June 2020

Ruohan Zhang

Papers citing "Widening the Pipeline in Human-Guided Reinforcement Learning with Explanation and Context-Aware Data Augmentation"

26 / 26 papers shown

Title
Learning from Active Human Involvement through Proxy Value Propagation Zhenghao Peng Wenjie Mo Chenda Duan Quanyi Li Bolei Zhou 156 15 0 05 Feb 2025
Symbols as a Lingua Franca for Bridging Human-AI Chasm for Explainable and Advisable AI Systems Subbarao Kambhampati S. Sreedharan Mudit Verma Yantian Zha L. Guan 83 49 0 21 Sep 2021
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training Kimin Lee Laura M. Smith Pieter Abbeel OffRL 58 284 0 09 Jun 2021
Representation Learning via Invariant Causal Mechanisms Jovana Mitrović Brian McWilliams Jacob Walker Lars Buesing Charles Blundell CML OOD SSL 58 249 0 15 Oct 2020
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases Senthil Purushwalkam Abhinav Gupta SSL 69 218 0 28 Jul 2020
Feature Expansive Reward Learning: Rethinking Human Input Andreea Bobu Marius Wiggert Claire Tomlin Anca Dragan 125 44 0 23 Jun 2020
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning Roberta Raileanu M. Goldstein Denis Yarats Ilya Kostrikov Rob Fergus OffRL 47 109 0 23 Jun 2020
Reinforcement Learning with Augmented Data Michael Laskin Kimin Lee Adam Stooke Lerrel Pinto Pieter Abbeel A. Srinivas OffRL 72 659 0 30 Apr 2020
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels Ilya Kostrikov Denis Yarats Rob Fergus OffRL 86 787 0 28 Apr 2020
Efficiently Guiding Imitation Learning Agents with Human Gaze Akanksha Saran Ruohan Zhang Elaine Schaertl Short S. Niekum 37 16 0 28 Feb 2020
FRESH: Interactive Reward Shaping in High-Dimensional State Spaces using Human Feedback Baicen Xiao Qifan Lu Bhaskar Ramasubramanian Andrew Clark L. Bushnell Radha Poovendran 39 25 0 19 Jan 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations P. Schramowski Wolfgang Stammer Stefano Teso Anna Brugger Xiaoting Shao Hans-Georg Luigs Anne-Katrin Mahlein Kristian Kersting 81 209 0 15 Jan 2020
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge Laura Rieger Chandan Singh W. James Murdoch Bin Yu FAtt 75 214 0 30 Sep 2019
Leveraging Human Guidance for Deep Reinforcement Learning Tasks Ruohan Zhang F. Torabi L. Guan D. Ballard Peter Stone 33 87 0 21 Sep 2019
Free-Lunch Saliency via Attention in Atari Agents Dmitry Nikulin A. Ianina Vladimir Aliev Sergey I. Nikolenko FAtt 48 24 0 07 Aug 2019
Deep Reinforcement Learning from Policy-Dependent Human Feedback Dilip Arumugam Jun Ki Lee S. Saskin Michael L. Littman 58 97 0 12 Feb 2019
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents F. Such Vashisht Madhavan Rosanne Liu Rui Wang Pablo Samuel Castro ... Jiale Zhi Ludwig Schubert Marc G. Bellemare Jeff Clune Joel Lehman OffRL 54 54 0 17 Dec 2018
DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback Riku Arakawa Sosuke Kobayashi Y. Unno Yuta Tsuboi S. Maeda 21 75 0 28 Oct 2018
AGIL: Learning Attention from Human for Visuomotor Tasks Ruohan Zhang Zhuode Liu Luxin Zhang Jake A. Whritner Karl S. Muller M. Hayhoe D. Ballard 42 76 0 01 Jun 2018
Visualizing and Understanding Atari Agents S. Greydanus Anurag Koul Jonathan Dodge Alan Fern FAtt 100 346 0 31 Oct 2017
Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces Garrett A. Warnell Nicholas R. Waytowich Vernon J. Lawhern Peter Stone 42 269 0 28 Sep 2017
A Brief Survey of Deep Reinforcement Learning Kai Arulkumaran M. Deisenroth Miles Brundage Anil Anthony Bharath OffRL 111 2,805 0 19 Aug 2017
Deep reinforcement learning from human preferences Paul Christiano Jan Leike Tom B. Brown Miljan Martic Shane Legg Dario Amodei 126 3,282 0 12 Jun 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 115 588 0 10 Mar 2017
Interactive Learning from Policy-Dependent Human Feedback J. MacGlashan Mark K. Ho R. Loftin Bei Peng Guan Wang David L. Roberts Matthew E. Taylor Michael L. Littman 68 303 0 21 Jan 2017
Prioritized Experience Replay Tom Schaul John Quan Ioannis Antonoglou David Silver OffRL 210 3,786 0 18 Nov 2015