Explainable Reinforcement Learning Through a Causal Lens

27 May 2019

Papers citing "Explainable Reinforcement Learning Through a Causal Lens"

30 / 80 papers shown

Title
Explaining Deep Reinforcement Learning Agents In The Atari Domain through a Surrogate Model Alexander Sieusahai Matthew J. Guzdial 40 13 0 07 Oct 2021
Collective eXplainable AI: Explaining Cooperative Strategies and Agent Contribution in Multiagent Reinforcement Learning with Shapley Values Alexandre Heuillet Fabien Couthouis Natalia Díaz Rodríguez 27 58 0 04 Oct 2021
Let the CAT out of the bag: Contrastive Attributed explanations for Text Saneem A. Chemmengath A. Azad Ronny Luss Amit Dhurandhar FAtt 34 10 0 16 Sep 2021
Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition Paul Festor Giulia Luise Matthieu Komorowski A. Faisal UD OffRL 34 11 0 16 Sep 2021
An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability Francesco Sovrano F. Vitali 45 30 0 11 Sep 2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey Richard Dazeley Peter Vamplew Francisco Cruz 32 61 0 20 Aug 2021
Improving Visualization Interpretation Using Counterfactuals Smiti Kaul D. Borland Nan Cao David Gotz CML 16 17 0 21 Jul 2021
Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi H. Siu Jaime D. Peña Edenna Chen Yutai Zhou Victor J. Lopez Kyle Palko K. Chang R. Allen 30 57 0 15 Jul 2021
Levels of explainable artificial intelligence for human-aligned conversational explanations Richard Dazeley Peter Vamplew Cameron Foale Charlotte Young Sunil Aryal F. Cruz 32 90 0 07 Jul 2021
Did I do that? Blame as a means to identify controlled effects in reinforcement learning Oriol Corcoll Youssef Mohamed Raul Vicente 26 3 0 01 Jun 2021
A Framework of Explanation Generation toward Reliable Autonomous Robots Tatsuya Sakai Kazuki Miyazawa Takato Horii Takayuki Nagai 27 8 0 06 May 2021
Explainable Autonomous Robots: A Survey and Perspective Tatsuya Sakai Takayuki Nagai 25 68 0 06 May 2021
Contrastive Explanations of Plans Through Model Restrictions Benjamin Krarup Senka Krivic Daniele Magazzeni D. Long Michael Cashmore David E. Smith 27 32 0 29 Mar 2021
Learning Symbolic Rules for Interpretable Deep Reinforcement Learning Zhihao Ma Yuzheng Zhuang Paul Weng Hankui Zhuo Dong Li Wulong Liu Jianye Hao NAI 51 14 0 15 Mar 2021
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods Nicholay Topin Stephanie Milani Fei Fang Manuela Veloso OffRL 29 33 0 25 Feb 2021
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs Thomas Spooner N. Vadori Sumitra Ganesh 30 7 0 20 Feb 2021
Training a Resilient Q-Network against Observational Interference Chao-Han Huck Yang I-Te Danny Hung Ouyang Yi Pin-Yu Chen OOD 31 14 0 18 Feb 2021
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research Markus Langer Daniel Oster Timo Speith Holger Hermanns Lena Kästner Eva Schmidt Andreas Sesing Kevin Baum XAI 68 415 0 15 Feb 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 53 170 0 13 Jan 2021
Sequential Explanations with Mental Model-Based Policies A. Yeung Shalmali Joshi Joseph Jay Williams Frank Rudzicz FAtt LRM 36 15 0 17 Jul 2020
Counterfactual Data Augmentation using Locally Factored Dynamics Silviu Pitis Elliot Creager Animesh Garg BDL OffRL 28 87 0 06 Jul 2020
Explainable robotic systems: Understanding goal-driven actions in a reinforcement learning scenario Francisco Cruz Richard Dazeley Peter Vamplew Ithan Moreira 15 40 0 24 Jun 2020
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps Tobias Huber Katharina Weitz Elisabeth André Ofra Amir FAtt 21 64 0 18 May 2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition Mahsan Nourani Chiradeep Roy Tahrima Rahman Eric D. Ragan Nicholas Ruozzi Vibhav Gogate AAML 19 17 0 05 May 2020
Self-Supervised Discovering of Interpretable Features for Reinforcement Learning Wenjie Shi Gao Huang Shiji Song Zhuoyuan Wang Tingyu Lin Cheng Wu SSL 28 18 0 16 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 32 213 0 09 Mar 2020
The Emerging Landscape of Explainable AI Planning and Decision Making Tathagata Chakraborti S. Sreedharan S. Kambhampati 35 112 0 26 Feb 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 76 14 0 04 Feb 2020
Interestingness Elements for Explainable Reinforcement Learning: Understanding Agents' Capabilities and Limitations Pedro Sequeira Melinda Gervasio 19 104 0 19 Dec 2019
Contrastive Explanation: A Structural-Model Approach Tim Miller CML 30 166 0 07 Nov 2018