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Reasoning with Inconsistent Possibilistic Ontologies by Applying Argument Accrual
DOI:
https://doi.org/10.24215/16666038.17.e16Keywords:
argument accrual, ontology reasoning, inconsistency handling, description logicsAbstract
We present an approach for performing instance checking in possibilistic description logic programming ontologies by accruing arguments that support the membership of individuals to concepts. Ontologies are interpreted as possibilistic logic programs where accruals of arguments as regarded as vertexes in an abstract argumentation framework. A suitable attack relation between accruals is defined. We present a reasoning framework with a case study and a Java-based implementation for enacting the proposed approach that is capable of reasoning under Dung’s grounded semantics.
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References
[1] X. Zhang, G. Xiao, Z. Lin, and J. V. den Bussche, “Inconsistency-tolerant reasoning with OWL-DL,”
International Journal of Approximate Reasoning, vol. 55, pp. 557–584, 2014.
[2] T. J. M. Bench-Capon and P. E. Dunne, “Argumentation in artificial intelligence,” Artificial Intelligence, vol. 171, no. 10-15, pp. 619–641, 2007.
[3] M. G. Lucero, C. I. Chesñevar, and G. R. Simari, “Modelling Argument Accrual in Possibilistic Defeasible Logic Programming,” in ECSQARU 2009, LNAI 5590 (C. S. ad G. Chemello, ed.), pp. 131–143, 2009.
[4] S. A. Gómez, “On the Application of Argument Accrual to Reasoning with Inconsistent Possibilistic Ontologies,” in Proc. of the XXII Argentinian Conference of Computer Science (CACIC 2016), pp. 14–23, Universidad Nacional de San Luis, oct 2016.
[5] B. Verheij, Rules, Reasons, Arguments: Formal studies of argumentation and defeat. PhD thesis, University of Maastricht, 1996.
[6] I. Letia and A. Groza, “Modelling Imprecise Arguments in Description Logics,” Advances in Electrical and Computer Engineering, vol. 9, no. 3, pp. 94–99, 2009.
[7] S. A. Gómez, C. I. Chesñevar, and G. R. Simari, “Reasoning with Inconsistent Ontologies Through Argumentation,” Applied Artificial Intelligence, vol. 1, no. 24, pp. 102–148, 2010.
[8] S. A. Gómez and G. R. Simari, “Merging of ontologies using belief revision and defeasible logic
programming,” Inteligencia Artificial, vol. 16, no. 52, pp. 16–28, 2013.
[9] S. A. Gómez, C. I. Chesñevar, and G. R. Simari, “ONTOarg: A Decision Support Framework for Ontology Integration based on Argumentation,” Expert Systems with Applications, vol. 40, pp. 1858–1870, 2013.
[10] D. Bryant, P. J. Krause, and G. Vreeswijk, “Argue tuProlog: A Lightweight Argumentation Engine for Agent Applications,” in Computational Models of Argument: Proceedings of COMMA 2006, 2006.
[11] M. Snaith and C. Reed, “TOAST: online ASPIC+ implementation,” in Proceedings of the 4th International Conference on Computational Models of Argument (COMMA 2012), IOS Press, 2012.
[12] N. Tamani and M. Croitoru, “Fuzzy argumentation system for decision support,” in Information
Processing and Management of Uncertainty in Knowledge-Based Systems, vol. 442, pp. 77–86, Communications in Computer and Information Science, 2014.
[13] F. Baader, D. Calvanese, D. McGuinness, D. Nardi, and P. Patel-Schneider, eds., The Description Logic Handbook – Theory, Implementation and Applications. Cambridge University Press, 2003.
[14] B. N. Grosof, I. Horrocks, R. Volz, and S. Decker, “Description Logic Programs: Combining Logic Programs with Description Logics,” WWW2003, May 20-24, Budapest, Hungary, 2003.
[15] S. Benferhat, Z. Bouraoui, S. Lagrue, and J. Rossit, “Merging Inconmensurable Possibilistic DL-Lite Assertional Bases,” in Proceedings of the IJCAI Workshop 13 Ontologies and Logic Programming for Query Answering (O. Papini, S. Benferhat, L. Garcia, and M.-L. Mugnier, eds.), pp. 90–95, 2015.
[16] S. A. Gómez, C. I. Chesñevar, and G. R. Simari, “Using Possibilistic Defeasible Logic Programming for Reasoning with Inconsistent Ontologies,” in Computer Science & Technology Series. XVII Argentine Congress of Computer Science Selected Papers (A. D. Giusti and J. Diaz, eds.), pp. 19–29, 2012.
[17] S. A. Gómez, “Towards a practical implementation of a reasoner for inconsistent possibilistic description logic programming ontologies,” in Proc. of the 2nd Argentinian Symposium of Ontologies
and their Applications (SAOA 2016), pp. 1–14, SADIO–45 JAIIO, sep 2016.
[18] T. Alsinet, C. I. Chesñevar, and L. Godo, “A level-based approach to computing warranted arguments in possibilistic defeasible logic programming,” in COMMA (P. Besnard, S. Doutre, and A. Hunter, eds.), vol. 172 of Frontiers in Artificial Intelligence and Applications, pp. 1–12, IOS Press, 2008.
[19] P. M. Dung, “On the aceptability of arguments and its fundamental role in nonmonotonic reasoning and logic programming,” in Proceedings of the 13th International Joint Conference in Artificial Intelligence (IJCAI), pp. 852–857, 1993.
International Journal of Approximate Reasoning, vol. 55, pp. 557–584, 2014.
[2] T. J. M. Bench-Capon and P. E. Dunne, “Argumentation in artificial intelligence,” Artificial Intelligence, vol. 171, no. 10-15, pp. 619–641, 2007.
[3] M. G. Lucero, C. I. Chesñevar, and G. R. Simari, “Modelling Argument Accrual in Possibilistic Defeasible Logic Programming,” in ECSQARU 2009, LNAI 5590 (C. S. ad G. Chemello, ed.), pp. 131–143, 2009.
[4] S. A. Gómez, “On the Application of Argument Accrual to Reasoning with Inconsistent Possibilistic Ontologies,” in Proc. of the XXII Argentinian Conference of Computer Science (CACIC 2016), pp. 14–23, Universidad Nacional de San Luis, oct 2016.
[5] B. Verheij, Rules, Reasons, Arguments: Formal studies of argumentation and defeat. PhD thesis, University of Maastricht, 1996.
[6] I. Letia and A. Groza, “Modelling Imprecise Arguments in Description Logics,” Advances in Electrical and Computer Engineering, vol. 9, no. 3, pp. 94–99, 2009.
[7] S. A. Gómez, C. I. Chesñevar, and G. R. Simari, “Reasoning with Inconsistent Ontologies Through Argumentation,” Applied Artificial Intelligence, vol. 1, no. 24, pp. 102–148, 2010.
[8] S. A. Gómez and G. R. Simari, “Merging of ontologies using belief revision and defeasible logic
programming,” Inteligencia Artificial, vol. 16, no. 52, pp. 16–28, 2013.
[9] S. A. Gómez, C. I. Chesñevar, and G. R. Simari, “ONTOarg: A Decision Support Framework for Ontology Integration based on Argumentation,” Expert Systems with Applications, vol. 40, pp. 1858–1870, 2013.
[10] D. Bryant, P. J. Krause, and G. Vreeswijk, “Argue tuProlog: A Lightweight Argumentation Engine for Agent Applications,” in Computational Models of Argument: Proceedings of COMMA 2006, 2006.
[11] M. Snaith and C. Reed, “TOAST: online ASPIC+ implementation,” in Proceedings of the 4th International Conference on Computational Models of Argument (COMMA 2012), IOS Press, 2012.
[12] N. Tamani and M. Croitoru, “Fuzzy argumentation system for decision support,” in Information
Processing and Management of Uncertainty in Knowledge-Based Systems, vol. 442, pp. 77–86, Communications in Computer and Information Science, 2014.
[13] F. Baader, D. Calvanese, D. McGuinness, D. Nardi, and P. Patel-Schneider, eds., The Description Logic Handbook – Theory, Implementation and Applications. Cambridge University Press, 2003.
[14] B. N. Grosof, I. Horrocks, R. Volz, and S. Decker, “Description Logic Programs: Combining Logic Programs with Description Logics,” WWW2003, May 20-24, Budapest, Hungary, 2003.
[15] S. Benferhat, Z. Bouraoui, S. Lagrue, and J. Rossit, “Merging Inconmensurable Possibilistic DL-Lite Assertional Bases,” in Proceedings of the IJCAI Workshop 13 Ontologies and Logic Programming for Query Answering (O. Papini, S. Benferhat, L. Garcia, and M.-L. Mugnier, eds.), pp. 90–95, 2015.
[16] S. A. Gómez, C. I. Chesñevar, and G. R. Simari, “Using Possibilistic Defeasible Logic Programming for Reasoning with Inconsistent Ontologies,” in Computer Science & Technology Series. XVII Argentine Congress of Computer Science Selected Papers (A. D. Giusti and J. Diaz, eds.), pp. 19–29, 2012.
[17] S. A. Gómez, “Towards a practical implementation of a reasoner for inconsistent possibilistic description logic programming ontologies,” in Proc. of the 2nd Argentinian Symposium of Ontologies
and their Applications (SAOA 2016), pp. 1–14, SADIO–45 JAIIO, sep 2016.
[18] T. Alsinet, C. I. Chesñevar, and L. Godo, “A level-based approach to computing warranted arguments in possibilistic defeasible logic programming,” in COMMA (P. Besnard, S. Doutre, and A. Hunter, eds.), vol. 172 of Frontiers in Artificial Intelligence and Applications, pp. 1–12, IOS Press, 2008.
[19] P. M. Dung, “On the aceptability of arguments and its fundamental role in nonmonotonic reasoning and logic programming,” in Proceedings of the 13th International Joint Conference in Artificial Intelligence (IJCAI), pp. 852–857, 1993.
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Published
2017-10-01
How to Cite
Gómez, S. A. (2017). Reasoning with Inconsistent Possibilistic Ontologies by Applying Argument Accrual. Journal of Computer Science and Technology, 17(02), e16. https://doi.org/10.24215/16666038.17.e16
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