Abstract
AAA is a sound and complete ABox abduction solver based on the Reiter’s MHS algorithm and the Pellet reasoner. It supports DL expressivity up to \(\mathcal {SROIQ}\) (i.e., OWL 2). It supports multiple observations, and allows to specify abducibles.
Similar content being viewed by others
Notes
All output file excerpts have been modified for readability: prefix part of IRIs were omitted and syntax of role assertions was rewritten to match this paper, some of the TIME DETAILS section have been cut off, and some outputs such as ontology statistics and other less relevant information has been removed. The shortcuts in TIME DETAILS are as follows: time—total time in seconds, n—number of nodes, ta—number of DL reasoner calls, r—reused models, p—pruned nodes.
References
Castano S, Espinosa Peraldí IS, Ferrara A, Karkaletsis V, Kaya A, Möller R, Montanelli S, Petasis G, Wessel M (2009) Multimedia interpretation for dynamic ontology evolution. J Log Comput 19(5):859–897
Cuenca Grau B, Horrocks I, Motik B, Parsia B, Patel-Schneider P, Sattler U (2008) OWL 2: the next step for OWL. J Web Semant 6(4):309–322
Del-Pinto W, Schmidt RA (2017) Forgetting-based abduction in \(\cal{ALC}\). In: Proceedings of the workshop on second-order quantifier elimination and related topics (SOQE 2017), Dresden, Germany, CEUR-WS, vol 2013, pp 27–35
Del-Pinto W, Schmidt RA (2019) Abox abduction via forgetting in ALC. In: The Thirty-Third AAAI conference on artificial intelligence, AAAI 2019, the thirty-first innovative applications of artificial intelligence conference, IAAI 2019, the ninth AAAI symposium on educational advances in artificial intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27–February 1, AAAI Press, 2019, pp 2768–2775
Donini FM, Massacci F (2000) Exptime tableaux for \(\cal{ALC}\). Artif Intell 124(1):87–138. https://doi.org/10.1016/S0004-3702(00)00070-9
Du J, Qi G, Shen Y, Pan JZ (2012) Towards practical ABox abduction in large description logic ontologies. Int J Semant Web Inf Syst 8(2):1–33
Elsenbroich C, Kutz O, Sattler U (2006) A case for abductive reasoning over ontologies. In: Proceedings of the OWLED*06 workshop on OWL: experiences and directions, Athens, GA, US, CEUR-WS, vol 216
Espinosa Peraldí IS, Kaya A, Möller R (2009) Formalizing multimedia interpretation based on abduction over description logic ABoxes. In: Proceedings of the 22nd international workshop on description logics (DL 2009), Oxford, UK, CEUR-WS, vol 477
Fabianová K, Pukancová J, Homola M (2019) Comparing ABox abduction based on minimal hitting set and MergeXplain. In: Proceedings of the 32nd international workshop on description logics, vol 2373, Oslo, Norway, June 18–21, 2019, CEUR-WS
Guo Y, Pan Z, Heflin J (2005) LUBM: a benchmark for OWL knowledge base systems. J Web Semant 3(2–3):158–182
Halland K, Britz K (2012) Abox abduction in \({\cal{ALC}}\) using a DL tableau. In: 2012 South African Institute of computer scientists and information technologists conference, SAICSIT ’12, Pretoria, South Africa, pp 51–58
Halland K, Britz K (2012) Naïve ABox abduction in \({\cal{ALC}}\) using a DL tableau. In: Proceedings of the 2012 international workshop on description logics, vol 846, DL 2012, Rome, Italy, CEUR-WS
Horrocks I, Kutz O, Sattler U (2006) The even more irresistible \({\cal{SROIQ}}\). In: Proceedings, tenth international conference on principles of knowledge representation and reasoning, Lake District of the United Kingdom, AAAI, pp 57–67
Hubauer T, Lamparter S, Pirker M (2011) Relaxed abduction: Robust information interpretation for incomplete models. In: Proceedings of the 24th iternational workshop on description logics (DL 2011), Barcelona, Spain, July 13–16, 2011
Kazakov Y (2008) RIQ and SROIQ are harder than SHOIQ. In: Brewka G, Lang J (eds) Principles of Knowledge Representation and Reasoning: proceedings of the eleventh international conference. AAAI Press, Sydney, pp 274–284
Klarman S, Endriss U, Schlobach S (2011) ABox abduction in the description logic \(\cal{ALC}\). J Autom Reason 46(1):43–80
Ma Y, Gu T, Xu B, Chang L (2012) An ABox abduction algorithm for the description logic \(\cal{ALCI}\). In: Intelligent information processing VI—7th IFIP TC 12 international conference, IIP 2012, Guilin, China. Proceedings, IFIP AICT, Springer, vol 385, pp 125–130
Mrózek D, Pukancová J, Homola M (2018) ABox abduction solver exploiting multiple DL reasoners. In: Proceedings of the 31st international workshop on description logics, Tempe, Arizona, US, CEUR-WS, vol 2211
Peirce CS (1878) Deduction, induction, and hypothesis. Pop Sci Mon 13:470–482
Petasis G, Möller R, Karkaletsis V (2013) BOEMIE: reasoning-based information extraction. In: Proceedings of the 1st workshop on natural language processing and automated reasoning co-located with 12th international conference on logic programming and nonmonotonic reasoning (LPNMR 2013), A Corunna, Spain, September 15th, 2013, pp 60–75
Pukancová J, Homola M (2015) Abductive reasoning with description logics: Use case in medical diagnosis. In: Proceedings of the 28th international workshop on description logics (DL 2015), Athens, Greece, CEUR-WS, vol 1350
Pukancová J, Homola M (2017) Tableau-based ABox abduction for the \({\cal{ALCHO}}\) description logic. In: Proceedings of the 30th international workshop on description logics, Montpellier, France, CEUR-WS, vol 1879
Pukancová J, Homola M (2018) ABox abduction for description logics: the case of multiple observations. In: Proceedings of the 31st international workshop on description logics, Tempe, Arizona, US, CEUR-WS, vol 2211
Pukancovái J (2018) Direct approach to ABox abduction in description logics. Ph.D. thesis, Comenius University in Bratislava
Reiter R (1987) A theory of diagnosis from first principles. Artif Intell 32(1):57–95
Schekotihin K, Rodler P, Schmid W (2018) Ontodebug: interactive ontology debugging plug-in for protégé. In: Foundations of information and knowledge systems—10th international symposium, FoIKS 2018, Budapest, Hungary, May 14–18, 2018, Proceedings, LNCS, Springer, vol 10833, pp 340–359
Shchekotykhin KM, Jannach D, Schmitz T (2015) MergeXplain: fast computation of multiple conflicts for diagnosis. In: Proceedings of the twenty-fourth international joint conference on artificial intelligence, IJCAI 2015, AAAI Press, Buenos Aires, Argentina
Sirin E, Parsia B, Cuenca Grau B, Kalyanpur A, Katz Y (2007) Pellet: a practical OWL-DL reasoner. J Web Semant 5(2):51–53
Acknowledgements
The authors wish to thank to Katarína Fabianová, Júlia Gablíková, and Drahomír Mrózek whose Master’s projects were affiliated with the AAA solver.
Funding
This work was supported from national projects VEGA 1/1333/12, VEGA 1/0778/18, and APVV-19-0220. Júlia Pukancová was also supported by the Comenius University Grants UK/426/2015 and UK/266/2018.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pukancová, J., Homola, M. The AAA ABox Abduction Solver. Künstl Intell 34, 517–522 (2020). https://doi.org/10.1007/s13218-020-00685-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13218-020-00685-4