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Article

A Defeasible Description Logic for Abduction

Published: 06 November 2023 Publication History

Abstract

In this work we introduce a defeasible Description Logic for abductive reasoning. Our proposal exploits a fragment of a probabilistic extension of a Description Logic of typicality, whose semantics corresponds to a natural extension of the well established mechanism of rational closure extended to Description Logics. The presence of typicality assertions that can be non-monotonically inferred from a knowledge base, corresponding to those belonging to its rational closure, avoids the need of an explicit selection of abducibles.

References

[1]
Azzolini D, Bellodi E, Ferilli S, Riguzzi F, and Zese R Abduction with probabilistic logic programming under the distribution semantics Int. J. Approx. Reason. 2022 142 41-63
[2]
Baader F and Hollunder B Priorities on defaults with prerequisites, and their application in treating specificity in terminological default logic J. Autom. Reason. (JAR) 1995 15 1 41-68
[3]
Baader, F., Calvanese, D., Mcguinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)
[4]
Bellodi E, Gavanelli M, Zese R, Lamma E, and Riguzzi F Nonground abductive logic programming with probabilistic integrity constraints Theory Pract. Logic Program. 2021 21 5 557-574
[5]
Bonatti PA, Faella M, Petrova I, and Sauro L A new semantics for overriding in description logics Artif. Intell. 2015 222 1-48
[6]
Bonatti PA, Lutz C, and Wolter F The complexity of circumscription in DLs J. Artif. Intell. Res. (JAIR) 2009 35 717-773
[7]
Brachman, R.J., Levesque, H.J.: Chapter 9 - structured descriptions. In: Brachman, R.J., Levesque, H.J. (eds.) Knowledge Representation and Reasoning, The Morgan Kaufmann Series in Artificial Intelligence, pp. 155–186. Morgan Kaufmann, San Francisco (2004).
[8]
Casini G and Straccia U Janhunen T and Niemelä I Rational closure for defeasible description logics Logics in Artificial Intelligence 2010 Heidelberg Springer 77-90
[9]
Casini G and Straccia U Defeasible inheritance-based description logics J. Artif. Intell. Res. (JAIR) 2013 48 415-473
[10]
Donini FM, Nardi D, and Rosati R Description logics of minimal knowledge and negation as failure ACM Trans. Comput. Logics (ToCL) 2002 3 2 177-225
[11]
Giordano L, Gliozzi V, Olivetti N, and Pozzato GL ALC+T: a preferential extension of description logics Fund. Inf. 2009 96 341-372
[12]
Giordano L, Gliozzi V, Olivetti N, and Pozzato GL Erdem E, Lin F, and Schaub T Prototypical reasoning with low complexity description logics: preliminary results Logic Programming and Nonmonotonic Reasoning 2009 Heidelberg Springer 430-436
[13]
Giordano, L., Gliozzi, V., Olivetti, N., Pozzato, G.L.: Reasoning about typicality in low complexity dls: the logics el and dl-lite t. In: Walsh, T. (ed.) IJCAI 2011, Proceedings of the 22nd International Joint Conference on Artificial Intelligence, Barcelona, Catalonia, Spain, 16–22 July 2011, pp. 894–899. IJCAI/AAAI (2011).
[14]
Giordano L, Gliozzi V, Olivetti N, and Pozzato GL A NonMonotonic description logic for reasoning about typicality Artif. Intell. 2013 195 165-202
[15]
Giordano L, Gliozzi V, Olivetti N, and Pozzato GL Semantic characterization of rational closure: from propositional logic to description logics Artif. Intell. 2015 226 1-33
[16]
Lehmann D and Magidor M What does a conditional knowledge base entail? Artif. Intell. 1992 55 1 1-60
[17]
Lieto A, Perrone F, Pozzato GL, and Chiodino E Beyond subgoaling: a dynamic knowledge generation framework for creative problem solving in cognitive architectures Cogn. Syst. Res. 2019 58 305-316
[18]
Lieto A and Pozzato GL A description logic framework for commonsense conceptual combination integrating typicality, probabilities and cognitive heuristics J. Exp. Theor. Artif. Intell. 2020 32 5 769-804
[19]
Lieto A, Pozzato GL, Striani M, Zoia S, and Damiano R DEGARI 2.0: a diversity-seeking, explainable, and affective art recommender for social inclusion Cogn. Syst. Res. 2023 77 1-17
[20]
Lieto A, Pozzato GL, Zoia S, Patti V, and Damiano R A commonsense reasoning framework for explanatory emotion attribution, generation and re-classification Knowl. Based Syst. 2021 227
[21]
Lieto, A., et al.: A sensemaking system for grouping and suggesting stories from multiple affective viewpoints in museums. Human-Comput. Interact., 1–35 (2023).
[22]
Lukasiewicz T Expressive probabilistic description logics Artif. Intell. 2008 172 6–7 852-883
[23]
Peirce CS Philosophical Writings of Peirce 1955 New York Dover Publications
[24]
Pozzato GL Antonucci A, Cholvy L, and Papini O Reasoning in description logics with typicalities and probabilities of exceptions Symbolic and Quantitative Approaches to Reasoning with Uncertainty 2017 Cham Springer 409-420
[25]
Pozzato G Typicalities and probabilities of exceptions in nonmotonic Description Logics Int. J. Approx. Reason. 2019 107 81-100
[26]
Riguzzi F, Bellodi E, Lamma E, and Zese R Probabilistic description logics under the distribution semantics Semant. Web 2015 6 5 477-501
[27]
Riguzzi F, Bellodi E, Lamma E, and Zese R Probabilistic description logics under the distribution semantics Semant. Web 2015 6 477-501
[28]
Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Reasoning with probabilistic ontologies. In: Yang, Q., Wooldridge, M. (eds.) Proceedings of IJCAI 2015, pp. 4310–4316. AAAI Press (2015). https://ijcai.org/proceedings/2015
[29]
Strasser C and Antonelli GA Zalta EN Non-monotonic logic The Stanford Encyclopedia of Philosophy 2018 Metaphysics Research Lab Stanford University
[30]
Studer R, Benjamins V, and Fensel D Knowledge engineering: principles and methods Data Knowl. Eng. 1998 25 1 161-197

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cover image Guide Proceedings
AIxIA 2023 – Advances in Artificial Intelligence: XXIInd International Conference of the Italian Association for Artificial Intelligence, AIxIA 2023, Rome, Italy, November 6–9, 2023, Proceedings
Nov 2023
498 pages
ISBN:978-3-031-47545-0
DOI:10.1007/978-3-031-47546-7
  • Editors:
  • Roberto Basili,
  • Domenico Lembo,
  • Carla Limongelli,
  • Andrea Orlandini

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 06 November 2023

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