Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning

9 December 2019

Papers citing "Exploratory Not Explanatory: Counterfactual Analysis of Saliency Maps for Deep Reinforcement Learning"

20 / 20 papers shown

Title
Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning Samuel Garcin Trevor A. McInroe Pablo Samuel Castro Prakash Panangaden Christopher G. Lucas David Abel Stefano V. Albrecht 56 0 0 08 Mar 2025
Policy-to-Language: Train LLMs to Explain Decisions with Flow-Matching Generated Rewards Xinyi Yang Liang Zeng Heng Dong Chao Yu X. Wu H. Yang Yu Wang Milind Tambe Tonghan Wang 76 2 0 18 Feb 2025
Revealing the Learning Process in Reinforcement Learning Agents Through Attention-Oriented Metrics Charlotte Beylier Simon M. Hofmann Nico Scherf 26 0 0 20 Jun 2024
Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables James Hinns David Martens 46 2 0 24 May 2024
Explainable AI (XAI) in Image Segmentation in Medicine, Industry, and Beyond: A Survey Rokas Gipiškis Chun-Wei Tsai Olga Kurasova 61 5 0 02 May 2024
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving Shahin Atakishiyev Mohammad Salameh Randy Goebel 72 6 0 18 Mar 2024
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 29 0 0 20 Nov 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges G. Vouros XAI 50 76 0 24 Jan 2023
Measuring Interventional Robustness in Reinforcement Learning Katherine Avery Jack Kenney Pracheta Amaranath Erica Cai David D. Jensen 21 0 0 19 Sep 2022
Look where you look! Saliency-guided Q-networks for generalization in visual Reinforcement Learning David Bertoin Adil Zouitine Mehdi Zouitine Emmanuel Rachelson 36 30 0 16 Sep 2022
Power and accountability in reinforcement learning applications to environmental policy Melissa S. Chapman Caleb Scoville Marcus Lapeyrolerie C. Boettiger OffRL 13 2 0 22 May 2022
Reinforcement Learning in Practice: Opportunities and Challenges Yuxi Li OffRL 36 9 0 23 Feb 2022
Detecting danger in gridworlds using Gromov's Link Condition Thomas F Burns R. Tang AI4CE 31 2 0 17 Jan 2022
Temporal-Spatial Causal Interpretations for Vision-Based Reinforcement Learning Wenjie Shi Gao Huang Shiji Song Cheng Wu 31 9 0 06 Dec 2021
Explainable Deep Reinforcement Learning for Portfolio Management: An Empirical Approach Mao Guan Xiao-Yang Liu AIFin AI4TS 19 20 0 07 Nov 2021
Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program Jeff Druce J. Niehaus Vanessa Moody David D. Jensen Michael L. Littman 13 15 0 10 Jun 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
Automatic Discovery of Interpretable Planning Strategies Julian Skirzyñski Frederic Becker Falk Lieder 13 15 0 24 May 2020
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations S. Sreedharan Utkarsh Soni Mudit Verma Siddharth Srivastava S. Kambhampati 73 30 0 04 Feb 2020
When Explanations Lie: Why Many Modified BP Attributions Fail Leon Sixt Maximilian Granz Tim Landgraf BDL FAtt XAI 13 132 0 20 Dec 2019