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Erschienen in:
Classical Algorithms for Reasoning and Explanation in Description Logics Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

Explainable AI Planning (XAIP): Overview and the Case of Contrastive Explanation (Extended Abstract)

verfasst von : Jörg Hoffmann, Daniele Magazzeni

Erschienen in: Reasoning Web. Explainable Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

Model-based approaches to AI are well suited to explainability in principle, given the explicit nature of their world knowledge and of the reasoning performed to take decisions. AI Planning in particular is relevant in this context as a generic approach to action-decision problems. Indeed, explainable AI Planning (XAIP) has received interest since more than a decade, and has been taking up speed recently along with the general trend to explainable AI. In the lecture, we provide an overview, categorizing and illustrating the different kinds of explanation relevant in AI Planning; and we outline recent works on one particular kind of XAIP, contrastive explanation. This extended abstract gives a brief summary of the lecture, with some literature pointers. We emphasize that completeness is neither claimed nor intended; the abstract may serve as a brief primer with literature entry points.

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Vorheriges Kapitel A Modest Markov Automata Tutorial
Fußnoten
Literatur
1.
Bercher, P., et al.: Plan, repair, execute, explain - how planning helps to assemble your home theater. In: Chien, S., Do, M., Fern, A., Ruml, W. (eds.) Proceedings of the 24th International Conference on Automated Planning and Scheduling (ICAPS 2014). AAAI Press (2014)
2.
Bidot, J., Biundo, S., Heinroth, T., Minker, W., Nothdurft, F., Schattenberg, B.: Verbal plan explanations for hybrid planning. In: Proceedings MKWI (2010)
3.
Cashmore, M., Collins, A., Krarup, B., Krivic, S., Magazzeni, D., Smith, D.: Explainable planning as a service. In: ICAPS-19 Workshop on Explainable Planning (2019)
4.
Chakraborti, T., Sreedharan, S., Zhang, Y., Kambhampati, S.: Plan explanations as model reconciliation: moving beyond explanation as soliloquy. In: Sierra, C. (ed.) Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017). AAAI Press/IJCAI (2017)
5.
Chakraborti, T., Kambhampati, S.: (how) can ai bots lie? In: Proceedings of the 2nd Workshop on Explainable Planning (XAIP 2019) (2019)
6.
Chakraborti, T., Kulkarni, A., Sreedharan, S., Smith, D.E., Kambhampati, S.: Explicability? Legibility? Predictability? Transparency? Privacy? Security? The emerging landscape of interpretable agent behavior. In: Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019). AAAI Press (2019)
7.
Chakraborti, T., Sreedharan, S., Grover, S., Kambhampati, S.: Plan explanations as model reconciliation. In: Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI 2019), pp. 258–266 (2019)
8.
Domshlak, C., Mirkis, V.: Deterministic oversubscription planning as heuristic search: abstractions and reformulations. J. Artif. Intell. Res. 52, 97–169 (2015)MathSciNetCrossRef
9.
Eifler, R., Cashmore, M., Hoffmann, J., Magazzeni, D., Steinmetz, M.: Explaining the space of plans through plan-property dependencies. In: Proceedings of the 2nd Workshop on Explainable Planning (XAIP 2019) (2019)
10.
Fox, M., Long, D., Magazzeni, D.: Explainable planning. In: Proceedings of IJCAI 2017 Workshop on Explainable AI (2017)
11.
Göbelbecker, M., Keller, T., Eyerich, P., Brenner, M., Nebel, B.: Coming up with good excuses: what to do when no plan can be found. In: Brafman, R.I., Geffner, H., Hoffmann, J., Kautz, H.A. (eds.) Proceedings of the 20th International Conference on Automated Planning and Scheduling (ICAPS 2010), pp. 81–88. AAAI Press (2010)
12.
Kambhampati, S.: Synthesizing explainable behavior for human-AI collaboration. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2019), pp. 1–2 (2019)
13.
Khan, O.Z., Poupart, P., Black, J.P.: Minimal sufficient explanations for factored Markov decision processes. In: Gerevini, A., Howe, A., Cesta, A., Refanidis, I. (eds.) Proceedings of the 19th International Conference on Automated Planning and Scheduling (ICAPS 2009). AAAI Press (2009)
14.
Krarup, B., Cashmore, M., Magazzeni, D., Miller, T.: Model-based contrastive explanations for explainable planning. In: ICAPS 2019 Workshop on Explainable Planning (2019)
15.
Kulkarni, A., Zha, Y., Chakraborti, T., Vadlamudi, S.G., Zhang, Y., Kambhampati, S.: Explicable planning as minimizing distance from expected behavior. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, AAMAS 2019, Montreal, QC, Canada, 13–17 May 2019, pp. 2075–2077 (2019)
16.
Langley, P., Meadows, B., Sridharan, M., Choi, D.: Explainable agency for intelligent autonomous systems. In: Singh, S., Markovitch, S. (eds.) Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI 2017). AAAI Press, February 2017
17.
McGuinness, D.L., Glass, A., Wolverton, M., da Silva, P.P.: Explaining task processing in cognitive assistants that learn. In: Proceedings of the 20th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2007), pp. 284–289 (2007)
18.
Miller, T.: Contrastive explanation: a structural-model approach. CoRR, abs/1811.03163 (2018)
19.
Miller, T.: Explanation in artificial intelligence: insights from the social sciences. Artif. Intell. 267, 1–38 (2019)MathSciNetCrossRef
20.
Nothdurft, F., Behnke, G., Bercher, P., Biundo, S., Minker, W.: The interplay of user-centered dialog systems and AI planning. In: Proceedings of the 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDAL2015), pp. 344–353 (2015)
21.
Petrick, R., Dalzel-Job, S., Hill, R.: Combining cognitive and affective measures with epistemic planning for explanation generation. In: Proceedings of the 2nd Workshop on Explainable Planning (XAIP 2019) (2019)
22.
Rosenthal, S., Selvaraj, S.P., Veloso, M.M.: Verbalization: narration of autonomous robot experience. In: Kambhampati, S. (ed.) Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016). AAAI Press/IJCAI (2016)
23.
Sarath, S., Alberto, O., Prasad, M., Subbarao, K.: Model-free model reconciliation. In: ICAPS-19 Workshop on Explainable Planning (2019)
24.
Seegebarth, B., Müller, F., Schattenberg, B., Biundo, S.: Making hybrid plans more clear to human users - A formal approach for generating sound explanations. In: Bonet, B., McCluskey, L., Silva, J.R., Williams, B. (eds.) Proceedings of the 22nd International Conference on Automated Planning and Scheduling (ICAPS 2012). AAAI Press (2012)
25.
Smith, D.: Planning as an iterative process. In: Hoffmann, J., Selman, B. (eds.) Proceedings of the 26th AAAI Conference on Artificial Intelligence (AAAI 2012), Toronto, ON, Canada, pp. 2180–2185. AAAI Press, July 2012
26.
Smith, D.E.: Choosing objectives in over-subscription planning. In: Koenig, S., Zilberstein, S., Koehler, J. (eds.) Proceedings of the 14th International Conference on Automated Planning and Scheduling (ICAPS 2004), Whistler, Canada, pp. 393–401. Morgan Kaufmann (2004)
27.
Sohrabi, S., Baier, J.A., McIlraith, S.A.: Preferred explanations: theory and generation via planning. In: Burgard, W., Roth, D. (eds.) Proceedings of the 25th National Conference of the American Association for Artificial Intelligence (AAAI 2011), San Francisco, CA, USA. AAAI Press, July 2011
28.
Sreedharan, S., Chakraborti, T., Kambhampati, S.: Handling model uncertainty and multiplicity in explanations via model reconciliation. In: Proceedings of the Twenty-Eighth International Conference on Automated Planning and Scheduling, ICAPS 2018, Delft, The Netherlands, 24–29 June 2018, pp. 518–526 (2018)
29.
Zhang, Y., Sreedharan, S., Kulkarni, A., Chakraborti, T., Zhuo, H., Kambhampati, S.: Plan explicability and predictability for robot task planning. In: Proceedings of ICRA (2017)
Metadaten
Titel
Explainable AI Planning (XAIP): Overview and the Case of Contrastive Explanation (Extended Abstract)
verfasst von
Jörg Hoffmann
Daniele Magazzeni
Copyright-Jahr
2019
Buch
Reasoning Web. Explainable Artificial Intelligence

Print ISBN: 978-3-030-31422-4

Electronic ISBN: 978-3-030-31423-1

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-31423-1_9

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