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In this paper, we provide a comprehensive outline of the different threads of work in Explainable AI Planning (XAIP) that has emerged as a focus area in the last couple of years and contrast that with earlier efforts in the field in terms of techniques, target users, and delivery mechanisms.
Mental models in human-computer interaction
John M Carroll and Judith Reitman Olson · 1988
Earlier work this paper cites.
A Classification of Plan Modification Strategies Based on Coverage and Information Requirements
Subbarao Kambhampati · 1990
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HTN planning: Complexity and Expressivity
Kutluhan Erol, James Hendler, and Dana S Nau · 1994
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Choosing Objectives in Over-Subscription Planning
David E Smith · 2004
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Minimal Sufficient Explanations for Factored Markov Decision Processes
Omar Zia Khan, Pascal Poupart, and James P Black · 2009
Earlier work this paper cites.
Coming Up with Good Excuses: What to Do When No Plan Can be Found
Moritz Göbelbecker, Thomas Keller, Patrick Eyerich, Michael Brenner, and Bernhard Nebel · 2010
Earlier work this paper cites.
Why do Humans Reason? Arguments for an Argumentative Theory
Hugo Mercier and Dan Sperber · 2011
Earlier work this paper cites.
Preferred Explanations: Theory and Generation via Planning
Shirin Sohrabi, Jorge A Baier, and Sheila A McIlraith · 2011
Earlier work this paper cites.
Making Hybrid Plans More Clear to Human Users – A Formal Approach for Generating Sound Explanations
Bastian Seegebarth, Felix Müller, Bernd Schattenberg, and Susanne Biundo · 2012
Earlier work this paper cites.
An English-Language Argumentation Interface for Explanation Generation with Markov Decision Processes in the Domain of Academic Advising
Thomas Dodson, Nicholas Mattei, Joshua T. Guerin, and Judy Goldsmith · 2013
Earlier work this paper cites.
Seeing Beyond Shadows: Incremental Abductive Reasoning for Plan Understanding
Ben Leon Meadows, Pat Langley, and Miranda Jane Emery · 2013
Earlier work this paper cites.
Plan, Repair, Execute, Explain – How Planning Helps to Assemble Your Home Theater
Pascal Bercher, Susanne Biundo, Thomas Geier, Thilo Hoernle, Florian Nothdurft, Felix Richter, and Bernd Schattenberg · 2014
Earlier work this paper cites.
Maintaining Evolving Domain Models
Dan Bryce, J Benton, and Michael W Boldt · 2016
Earlier work this paper cites.
Algorithmic transparency via quantitative input influence: Theory and experiments with learning systems
Anupam Datta, Shayak Sen, and Yair Zick · 2016
Earlier work this paper cites.
“Why Should I Trust You?” Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
Earlier work this paper cites.
Verbalization: Narration of Autonomous Robot Experience
Stephanie Rosenthal, Sai P Selvaraj, and Manuela M Veloso · 2016
Earlier work this paper cites.
Graying the Black Box: Understanding DQNs
Tom Zahavy, Nir Ben-Zrihem, and Shie Mannor · 2016
Earlier work this paper cites.
Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy
Tathagata Chakraborti, Sarath Sreedharan, Yu Zhang, and Subbarao Kambhampati · 2017
Earlier work this paper cites.
Unsolvability Certificates for Classical Planning
Salomé Eriksson, Gabriele Röger, and Malte Helmert · 2017
Earlier work this paper cites.
Explainable Artificial Intelligence (XAI)
David Gunning · 2017
Earlier work this paper cites.
Robot Task Planning and Explanation in Open and Uncertain Worlds
Marc Hanheide, Moritz Göbelbecker, Graham S Horn, Andrzej Pronobis, Kristoffer Sjöö, Alper Aydemir, Patric Jensfelt, Charles Gretton, Richard Dearden, Miroslav Janicek, et al · 2017
Earlier work this paper cites.
Improving Robot Controller Transparency Through Autonomous Policy Explanation
Bradley Hayes and Julie A Shah · 2017
Earlier work this paper cites.
Explainable Agency for Intelligent Autonomous Systems
Pat Langley, Ben Meadows, Mohan Sridharan, and Dongkyu Choi · 2017
Earlier work this paper cites.
Web Planner: A Tool to Develop Classical Planning Domains and Visualize Heuristic State-Space Search
Maurıcio C Magnaguagno, Ramon Fraga Pereira, Martin D Móre, and Felipe Meneguzzi · 2017
Cited alongside, same era.
Wojciech Samek, Thomas Wiegand, and Klaus-Robert Müller · 2017
Cited alongside, same era.
Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR
Sandra Wachter, Brent Mittelstadt, and Chris Russell · 2017
Cited alongside, same era.
Plan Explicability and Predictability for Robot Task Planning
Yu Zhang, Sarath Sreedharan, Anagha Kulkarni, Tathagata Chakraborti, Hankz Hankui Zhuo, and Subbarao Kambhampati · 2017
Cited alongside, same era.
Explaining Rebel Behavior in Goal Reasoning Agents
Dustin Dannenhauer, Michael W Floyd, Daniele Magazzeni, and David W Aha · 2018
Cited alongside, same era.
Balancing Explanations and Explicability in Human-Aware Planning
Tathagata Chakraborti, Sarath Sreedharan, and Subbarao Kambhampati · 2019
Later among the works it cites.
DARPA’s Explainable Artificial Intelligence Program
David Gunning and David W Aha · 2019
Later among the works it cites.
Explainable AI Planning (XAIP): Overview and the Case of Contrastive Explanation
Jörg Hoffmann and Daniele Magazzeni · 2019
Later among the works it cites.
Explainable Reinforcement Learning via Reward Decomposition
Zoe Juozapaitis, Anurag Koul, Alan Fern, Martin Erwig, and Finale Doshi-Velez · 2019
Later among the works it cites.
Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations
Joseph Kim, Christian Muise, Ankit Shah, Shubham Agarwal, and Julie Shah · 2019
Later among the works it cites.
Model-Based Contrastive Explanations for Explainable Planning
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A Proof System for Unsolvable Planning Tasks
Salomé Eriksson, Gabriele Röger, and Malte Helmert · 2018
Cited alongside, same era.
How Explainable Plans Can Make Planning Faster
Antoine Grea, Laëtitia Matignon, and Samir Aknine · 2018
Cited alongside, same era.
Visualizing and Understanding Atari Agents
Samuel Greydanus, Anurag Koul, Jonathan Dodge, and Alan Fern · 2018
Cited alongside, same era.
What Can Automated Planning do for Intelligent Tutoring Systems?
Sachin Grover, Tathagata Chakraborti, and Subbarao Kambhampati · 2018
Cited alongside, same era.
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, and Rory Sayres · 2018
Cited alongside, same era.
Learning Finite State Representations of Recurrent Policy Networks
Anurag Koul, Sam Greydanus, and Alan Fern · 2018
Cited alongside, same era.
What was I planning to do?
Raymond Sheh David Aha Piyabutra Jampathom Keith Akins Eric Sydow Vikas Shivashankar Mark Roberts, Isaac Monteath and Claude Sammut · 2018
Cited alongside, same era.
Benjamin Krarup, Michael Cashmore, Daniele Magazzeni, and Tim Miller · 2019
Later among the works it cites.
Design for Interpretability
Anagha Kulkarni, Sarath Sreedharan, Sarah Keren, Tathagata Chakraborti, David E. Smith, and Subbarao Kambhampati · 2019
Later among the works it cites.
Exploring computational user models for agent policy summarization
Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, and Ofra Amir · 2019
Later among the works it cites.
Varieties of explainable agency
Pat Langley · 2019
Later among the works it cites.
Explanation in Artificial Intelligence: Insights from the Social Sciences
Tim Miller · 2019
Later among the works it cites.
Model-Free Model Reconciliation
Sarath Sreedharan, Alberto Olmo Hernandez, Aditya Prasad Mishra, and Subbarao Kambhampati · 2019
Later among the works it cites.
Why Can’t You Do That HAL? Explaining Unsolvability of Planning Tasks
Sarath Sreedharan, Siddharth Srivastava, David Smith, and Subbarao Kambhampati · 2019
Later among the works it cites.
Generation of Policy-Level Explanations for Reinforcement Learning
Nicholay Topin and Manuela Veloso · 2019
Later among the works it cites.
A Preliminary Logic-based Approach for Explanation Generation
Stylianos Vasileiou, William Yeoh, and Tran Cao Son · 2019
Later among the works it cites.
Towards Understanding User Preferences for Explanation Types in Explanation as Model Reconciliation
Zahra Zahedi, Alberto Olmo, Tathagata Chakraborti, Sarath Sreedharan, and Subbarao Kambhampati · 2019
Later among the works it cites.
A New Approach to Plan-Space Explanation: Analyzing Plan-Property Dependencies in Oversubscription Planning
Rebecca Eifler, Michael Cashmore, Jörg Hoffmann, Daniele Magazzeni, and Marcel Steinmetz · 2020
Closest in time.
RADAR: Automated Task Planning for Proactive Decision Support
Sachin Grover, Sailik Sengupta, Tathagata Chakraborti, Aditya Prasad Mishra, and Subbarao Kambhampati · 2020
Closest in time.
Explainable Reinforcement Learning Through a Causal Lens
Prashan Madumal, Tim Miller, Liz Sonenberg, and Frank Vetere · 2020
Closest in time.
Expectation-Aware Planning: A Unifying Framework for Synthesizing and Executing Self-Explaining Plans for Human-Aware Planning
Sarath Sreedharan, Tathagata Chakraborti, Christian Muise, and Subbarao Kambhampati · 2020
Closest in time.
D3WA+: A Case Study of XAIP in a Model Acquisition Task
Sarath Sreedharan, Tathagata Chakraborti, Christian Muise, Yasaman Khazaeni, and Subbarao Kambhampati · 2020
Closest in time.
TLdR: Policy Summarization for Factored SSP Problems Using Temporal Abstractions
Sarath Sreedharan, Siddharth Srivastava, and Subbarao Kambhampati · 2020
Closest in time.
Different “Intelligibility” for Different Folks
Yishan Zhou and David Danks · 2020
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