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We introduce a novel framework for causal explanations of stochastic, sequential decision-making systems built on the well-studied structural causal model paradigm for causal reasoning.
Teoria statistica delle classi e calcolo delle probabilita
Carlo Bonferroni. 1936 · 1936
Earlier work this paper cites.
On a test of whether one of two random variables is stochastically larger than the other
Henry B Mann and Donald R Whitney. 1947 · 1947
Earlier work this paper cites.
On the theory of dynamic programming
Richard Bellman. 1952 · 1952
Earlier work this paper cites.
The psychology of interpersonal relations
Fritz Heider. 1958 · 1958
Earlier work this paper cites.
Causation
David Lewis. 1974 · 1974
Earlier work this paper cites.
The cement of the universe: A study of causation
John Leslie Mackie. 1980 · 1980
Earlier work this paper cites.
Knowledge-based causal attribution: The abnormal conditions focus model
Denis J Hilton and Ben R Slugoski. 1986 · 1986
Earlier work this paper cites.
Causality in device behavior
Yumi Iwasaki and Herbert A Simon. 1986 · 1986
Earlier work this paper cites.
The problem of causal selection
Germund Hesslow. 1988 · 1988
Earlier work this paper cites.
Conversational processes and causal explanation
Denis J Hilton. 1990 · 1990
Earlier work this paper cites.
Contrastive explanation
Peter Lipton. 1990 · 1990
Earlier work this paper cites.
Mental models and causal explanation: Judgements of probable cause and explanatory relevance
Denis J Hilton. 1996 · 1996
Earlier work this paper cites.
Causal ordering for multiple mode systems. In Proceedings of the Eleventh International Workshop on Qualitative Reasoning . 203–214
Louise Trave-Massuyes and Renaud Pons. 1997 · 1997
Earlier work this paper cites.
Responsibility and blame: A structural-model approach
Hana Chockler and Joseph Y Halpern. 2004 · 2004
Earlier work this paper cites.
Conditional logic of actions and causation
Laura Giordano and Camilla Schwind. 2004 · 2004
Earlier work this paper cites.
Causes and explanations: A structural-model approach. Part I: Causes
Joseph Y Halpern and Judea Pearl. 2005a · 2005
Earlier work this paper cites.
Causes and explanations: A structural-model approach. Part II: Explanations
Joseph Y Halpern and Judea Pearl. 2005b · 2005
Earlier work this paper cites.
Making things happen: A theory of causal explanation
James Woodward. 2005 · 2005
Earlier work this paper cites.
Causes and explanations in the structural-model approach: Tractable cases
Thomas Eiter and Thomas Lukasiewicz. 2006 · 2006
Cited alongside, same era.
Human-automation collaboration in dynamic mission planning: A challenge requiring an ecological approach
Michael P Linegang, Heather A Stoner, Michael J Patterson, Bobbie D Seppelt, Joshua D Hoffman, Zachariah B Crittendon, and John D Lee. 2006 · 2006
Cited alongside, same era.
The structure and function of explanations
Tania Lombrozo. 2006 · 2006
Cited alongside, same era.
Four decades of scientific explanation
Wesley C Salmon. 2006 · 2006
Cited alongside, same era.
Statistical models for causation
David A Freedman. 2007 · 2007
Cited alongside, same era.
Autonomy and common ground in human-robot interaction: A field study
Kristen Stubbs, Pamela J Hinds, and David Wettergreen. 2007 · 2007
Cited alongside, same era.
Situation awareness-based agent transparency and human-autonomy teaming effectiveness
Jessie YC Chen, Shan G Lakhmani, Kimberly Stowers, Anthony R Selkowitz, Julia L Wright, and Michael Barnes. 2018 · 2018
Later among the works it cites.
An Environment for Autonomous Driving Decision-Making
Edouard Leurent. 2018 · 2018
Later among the works it cites.
Explicability? legibility? predictability? transparency? privacy? security? the emerging landscape of interpretable agent behavior. In International Conference on Automated Planning and Scheduling (ICAPS) . 86–96
Tathagata Chakraborti, Anagha Kulkarni, Sarath Sreedharan, David E Smith, and Subbarao Kambhampati. 2019 · 2019
Later among the works it cites.
Causal inference by string diagram surgery. In International Conference on Foundations of Software Science and Computation Structures . Springer, 313–329
Bart Jacobs, Aleks Kissinger, and Fabio Zanasi. 2019 · 2019
Later among the works it cites.
Explainable reinforcement learning via reward decomposition. In IJCAI/ECAI Workshop on Explainable Artificial Intelligence
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Generating explanations based on Markov decision processes. In Mexican International Conference on Artificial Intelligence . Springer, 51–62
Francisco Elizalde, Enrique Sucar, Julieta Noguez, and Alberto Reyes. 2009 · 2009
Cited alongside, same era.
Minimal sufficient explanations for factored Markov decision processes. In International Conference on Automated Planning and Scheduling (ICAPS) , Vol. 19
Omar Khan, Pascal Poupart, and James Black. 2009 · 2009
Cited alongside, same era.
Causal-explanatory pluralism: How intentions, functions, and mechanisms influence causal ascriptions
Tania Lombrozo. 2010 · 2010
Cited alongside, same era.
Explanation and abductive inference
Tania Lombrozo. 2012 · 2012
Cited alongside, same era.
The hazards of explanation: Overgeneralization in the face of exceptions
Joseph Jay Williams, Tania Lombrozo, and Bob Rehder. 2013 · 2013
Cited alongside, same era.
A modification of the Halpern-Pearl definition of causality. In Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI) . 3022–3033
Joseph Halpern. 2015 · 2015
Cited alongside, same era.
Zoe Juozapaitis, Anurag Koul, Alan Fern, Martin Erwig, and Finale Doshi-Velez. 2019 · 2019
Later among the works it cites.
Explanation in artificial intelligence: Insights from the social sciences
Tim Miller. 2019 · 2019
Later among the works it cites.
Explaining explanations in AI. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency . 279–288
Brent Mittelstadt, Chris Russell, and Sandra Wachter. 2019 · 2019
Later among the works it cites.
Explaining reward functions in Markov decision processes. In Thirty-Second International FLAIRS Conference
Jacob Russell and Eugene Santos. 2019 · 2019
Later among the works it cites.
Causality-based Explanation of Classification Outcomes
Leopoldo Bertossi, Jordan Li, Maximilian Schleich, Dan Suciu, and Zografoula Vagena. 2020 · 2020
Later among the works it cites.
The emerging landscape of explainable automated planning & decision making. In International Joint Conference on Artificial Intelligence (IJCAI) . 4803–4811
Tathagata Chakraborti, Sarath Sreedharan, and Subbarao Kambhampati. 2020 · 2020
Later among the works it cites.
Why does my model fail? Contrastive local explanations for retail forecasting. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency . 90–98
Ana Lucic, Hinda Haned, and Maarten de Rijke. 2020 · 2020
Later among the works it cites.
Explainable reinforcement learning through a causal lens. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 34. 2493–2500
Prashan Madumal, Tim Miller, Liz Sonenberg, and Frank Vetere. 2020 · 2020
Later among the works it cites.
Explaining machine learning classifiers through diverse counterfactual explanations. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency . 607–617
Ramaravind K Mothilal, Amit Sharma, and Chenhao Tan. 2020 · 2020
Later among the works it cites.
Doctor XAI: An ontology-based approach to black-box sequential data classification explanations. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency . 629–639
Cecilia Panigutti, Alan Perotti, and Dino Pedreschi. 2020 · 2020
Later among the works it cites.
Hadrien Pouget, Hana Chockler, Youcheng Sun, and Daniel Kroening. 2020 · 2020
Later among the works it cites.
Yunfeng Zhang, Q Vera Liao, and Rachel KE Bellamy. 2020 · 2020
Later among the works it cites.
Algorithmic recourse: From counterfactual explanations to interventions. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency . 353–362
Amir-Hossein Karimi, Bernhard Schölkopf, and Isabel Valera. 2021 · 2021
Later among the works it cites.
On the Equivalence of Causal Models: A Category-Theoretic Approach
Jun Otsuka and Hayato Saigo. 2022 · 2022
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