Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution

23 December 2019

Papers citing "Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution"

41 / 41 papers shown

Title
Neuro-Symbolic Generation of Explanations for Robot Policies with Weighted Signal Temporal Logic Mikihisa Yuasa R. Sreenivas Huy T. Tran 40 0 0 30 Apr 2025
Pay Attention to What and Where? Interpretable Feature Extractor in Vision-based Deep Reinforcement Learning Tien Pham Angelo Cangelosi 31 0 0 14 Apr 2025
Éxplaining RL Decisions with Trajectories': A Reproducibility Study Karim Abdel Sadek Matteo Nulli Joan Velja Jort Vincenti 38 0 0 11 Nov 2024
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
RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation Zelei Cheng Xian Wu Jiahao Yu Sabrina Yang Gang Wang Xinyu Xing OffRL 26 2 0 05 May 2024
How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps Romy Müller HAI 45 6 0 03 Apr 2024
XRL-Bench: A Benchmark for Evaluating and Comparing Explainable Reinforcement Learning Techniques Yu Xiong Zhipeng Hu Ye Huang Runze Wu Kai Guan ... Tianze Zhou Yujing Hu Haoyu Liu Tangjie Lyu Changjie Fan OffRL 62 1 0 20 Feb 2024
ACTER: Diverse and Actionable Counterfactual Sequences for Explaining and Diagnosing RL Policies Jasmina Gajcin Ivana Dusparic CML OffRL 30 2 0 09 Feb 2024
Explaining Reinforcement Learning Agents Through Counterfactual Action Outcomes Yotam Amitai Yael Septon Ofra Amir CML 17 5 0 18 Dec 2023
Counterfactual Explanation Policies in RL Shripad Deshmukh R Srivatsan Supriti Vijay Jayakumar Subramanian Chirag Agarwal OffRL 35 0 0 25 Jul 2023
Explaining RL Decisions with Trajectories Shripad Deshmukh Arpan Dasgupta Balaji Krishnamurthy Nan Jiang Chirag Agarwal Georgios Theocharous J. Subramanian OffRL 25 3 0 06 May 2023
CrystalBox: Future-Based Explanations for Input-Driven Deep RL Systems Sagar Patel Sangeetha Abdu Jyothi Nina Narodytska OffRL 11 0 0 27 Feb 2023
GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations Tobias Huber Maximilian Demmler Silvan Mertes Matthew Lyle Olson Elisabeth André 12 14 0 24 Feb 2023
Explainable Deep Reinforcement Learning: State of the Art and Challenges G. Vouros XAI 50 76 0 24 Jan 2023
PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Markets Shuo Sun Molei Qin Xinrun Wang Bo An FaML OffRL AIFin 24 4 0 14 Jan 2023
Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information V. Sharma John P. Dickerson Pratap Tokekar AI4CE 11 0 0 09 Nov 2022
Causal Explanation for Reinforcement Learning: Quantifying State and Temporal Importance Xiaoxiao Wang Fanyu Meng Xin Liu Z. Kong Xin Chen XAI CML FAtt 39 4 0 24 Oct 2022
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities Jasmina Gajcin Ivana Dusparic CML OffRL 35 8 0 21 Oct 2022
Integrating Policy Summaries with Reward Decomposition for Explaining Reinforcement Learning Agents Yael Septon Tobias Huber Elisabeth André Ofra Amir FAtt 10 9 0 21 Oct 2022
Neural Distillation as a State Representation Bottleneck in Reinforcement Learning Valentin Guillet D. Wilson Carlos Aguilar-Melchor Emmanuel Rachelson 13 1 0 05 Oct 2022
Human-AI Shared Control via Policy Dissection Quanyi Li Zhenghao Peng Haibin Wu Lan Feng Bolei Zhou 18 13 0 31 May 2022
Policy Distillation with Selective Input Gradient Regularization for Efficient Interpretability Jinwei Xing Takashi Nagata Xinyun Zou Emre Neftci J. Krichmar AAML 20 4 0 18 May 2022
ReCCoVER: Detecting Causal Confusion for Explainable Reinforcement Learning Jasmina Gajcin Ivana Dusparic CML 43 6 0 21 Mar 2022
Lazy-MDPs: Towards Interpretable Reinforcement Learning by Learning When to Act Alexis Jacq Johan Ferret Olivier Pietquin M. Geist 24 9 0 16 Mar 2022
Reinforcement Learning in Practice: Opportunities and Challenges Yuxi Li OffRL 36 9 0 23 Feb 2022
Explaining Reinforcement Learning Policies through Counterfactual Trajectories Julius Frost Olivia Watkins Eric Weiner Pieter Abbeel Trevor Darrell Bryan A. Plummer Kate Saenko OffRL 36 5 0 29 Jan 2022
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI Meike Nauta Jan Trienes Shreyasi Pathak Elisa Nguyen Michelle Peters Yasmin Schmitt Jorg Schlotterer M. V. Keulen C. Seifert ELM XAI 28 396 0 20 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
Acquisition of Chess Knowledge in AlphaZero Thomas McGrath A. Kapishnikov Nenad Tomašev Adam Pearce Demis Hassabis Been Kim Ulrich Paquet Vladimir Kramnik 28 159 0 17 Nov 2021
Counterfactual Explanations in Sequential Decision Making Under Uncertainty Stratis Tsirtsis A. De Manuel Gomez Rodriguez 19 45 0 06 Jul 2021
The Atari Data Scraper B. Pierson J. Ventura Matthew E. Taylor OnRL 13 0 0 11 Apr 2021
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond Xuhong Li Haoyi Xiong Xingjian Li Xuanyu Wu Xiao Zhang Ji Liu Jiang Bian Dejing Dou AAML FaML XAI HAI 23 317 0 19 Mar 2021
Benchmarking Perturbation-based Saliency Maps for Explaining Atari Agents Tobias Huber Benedikt Limmer Elisabeth André FAtt 20 14 0 18 Jan 2021
Observation Space Matters: Benchmark and Optimization Algorithm J. Kim Sehoon Ha OOD OffRL 18 11 0 02 Nov 2020
Machine versus Human Attention in Deep Reinforcement Learning Tasks Sihang Guo Ruohan Zhang Bo Liu Yifeng Zhu M. Hayhoe D. Ballard Peter Stone OffRL 24 25 0 29 Oct 2020
Towards falsifiable interpretability research Matthew L. Leavitt Ari S. Morcos AAML AI4CE 13 67 0 22 Oct 2020
Reconstructing Actions To Explain Deep Reinforcement Learning Xuan Chen Zifan Wang Yucai Fan Bonan Jin Piotr (Peter) Mardziel Carlee Joe-Wong Anupam Datta FAtt 13 2 0 17 Sep 2020
SOAC: The Soft Option Actor-Critic Architecture Chenghao Li Xiaoteng Ma Chongjie Zhang Jun Yang L. Xia Qianchuan Zhao 20 6 0 25 Jun 2020
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
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation Tianhong Dai Kai Arulkumaran Tamara Gerbert Samyakh Tukra Feryal M. P. Behbahani Anil Anthony Bharath 14 27 0 18 Dec 2019