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Local Explanations for Reinforcement Learning

8 February 2022

Papers citing "Local Explanations for Reinforcement Learning"

20 / 20 papers shown

Title
A Survey on the Explainability of Supervised Machine Learning Nadia Burkart Marco F. Huber FaML XAI 55 775 0 16 Nov 2020
What Did You Think Would Happen? Explaining Agent Behaviour Through Intended Outcomes Herman Yau Chris Russell Simon Hadfield FAtt LRM 47 38 0 10 Nov 2020
Re-understanding Finite-State Representations of Recurrent Policy Networks Mohamad H. Danesh Anurag Koul Alan Fern Saeed Khorram 67 21 0 06 Jun 2020
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps Tobias Huber Katharina Weitz Elisabeth André Ofra Amir FAtt 62 67 0 18 May 2020
Towards Interpretable Reinforcement Learning Using Attention Augmented Agents Alex Mott Daniel Zoran Mike Chrzanowski Daan Wierstra Danilo Jimenez Rezende 66 190 0 06 Jun 2019
Exploring Computational User Models for Agent Policy Summarization Isaac Lage Daphna Lifschitz Finale Doshi-Velez Ofra Amir LLMAG 69 76 0 30 May 2019
Explainable Reinforcement Learning Through a Causal Lens Prashan Madumal Tim Miller L. Sonenberg F. Vetere CML 103 361 0 27 May 2019
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents Christian Rupprecht Cyril Ibrahim C. Pal 78 32 0 02 Apr 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 148 1,328 0 26 Feb 2019
Learning Finite State Representations of Recurrent Policy Networks Anurag Koul S. Greydanus Alan Fern 46 88 0 29 Nov 2018
Establishing Appropriate Trust via Critical States Sandy H. Huang Kush S. Bhatia Pieter Abbeel Anca Dragan OffRL 70 111 0 18 Oct 2018
Verifiable Reinforcement Learning via Policy Extraction Osbert Bastani Yewen Pu Armando Solar-Lezama OffRL 134 338 0 22 May 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 126 591 0 21 Feb 2018
Visualizing and Understanding Atari Agents S. Greydanus Anurag Koul Jonathan Dodge Alan Fern FAtt 114 347 0 31 Oct 2017
TIP: Typifying the Interpretability of Procedures Amit Dhurandhar Vijay Iyengar Ronny Luss Karthikeyan Shanmugam 51 36 0 09 Jun 2017
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016
OpenAI Gym Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang Wojciech Zaremba OffRL ODL 223 5,086 0 05 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,033 0 16 Feb 2016
State of the Art Control of Atari Games Using Shallow Reinforcement Learning Yitao Liang Marlos C. Machado Erik Talvitie Michael Bowling 72 113 0 04 Dec 2015
A Tutorial on Spectral Clustering U. V. Luxburg 290 10,543 0 01 Nov 2007