How does incoherence affect inconsistency-tolerant semantics for Datalog±?

The concept of incoherence naturally arises in ontological settings, specially when integrating knowledge. In the Datalog± literature, however, this is an issue that is yet to be studied more deeply. The main focus of our work is to show how classical inconsistency-tolerant semantics for query answering behaves when dealing with atoms that are relevant to unsatisfiable sets of existential rules, which may hamper the quality of answers and any reasoning task based on those semantics. We also propose a notion of incoherency-tolerant semantics for query answering in Datalog±, and exemplify this notion with a particular semantics based on the transformation of classic Datalog± ontologies into defeasible Datalog± ones, which use argumentation as its reasoning machinery.

[1]  Guillermo Ricardo Simari,et al.  Inconsistency-Tolerant Reasoning in Datalog ^± ± Ontologies via an Argumentative Semantics , 2014, IBERAMIA.

[2]  Andrea Calì,et al.  On the decidability and complexity of query answering over inconsistent and incomplete databases , 2003, PODS.

[3]  Henry Prakken,et al.  Argument-Based Extended Logic Programming with Defeasible Priorities , 1997, J. Appl. Non Class. Logics.

[4]  Stefan Schlobach,et al.  Non-Standard Reasoning Services for the Debugging of Description Logic Terminologies , 2003, IJCAI.

[5]  Sébastien Konieczny,et al.  Merging Information Under Constraints: A Logical Framework , 2002, J. Log. Comput..

[6]  Maurizio Lenzerini,et al.  Inconsistency-Tolerant Semantics for Description Logics , 2010, RR.

[7]  Guillermo Ricardo Simari,et al.  Defeasible logic programming: an argumentative approach , 2003, Theory and Practice of Logic Programming.

[8]  Guillermo Ricardo Simari,et al.  Datalog+- Ontology Consolidation , 2016, J. Artif. Intell. Res..

[9]  Riccardo Rosati,et al.  On the Complexity of Dealing with Inconsistency in Description Logic Ontologies , 2011, IJCAI.

[10]  Trevor J. M. Bench-Capon,et al.  Argumentation in artificial intelligence , 2007, Artif. Intell..

[11]  Guilin Qi,et al.  Approaches to Inconsistency Handling in Description-Logic Based Ontologies , 2007, OTM Workshops.

[12]  Andrea Calì,et al.  A general datalog-based framework for tractable query answering over ontologies , 2009, SEBD.

[13]  Guillermo Ricardo Simari,et al.  Argumentation in Artificial Intelligence , 2009 .

[14]  Michael Wooldridge,et al.  Complexity of Abstract Argumentation , 2009, Argumentation in Artificial Intelligence.

[15]  Phan Minh Dung,et al.  On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games , 1995, Artif. Intell..

[16]  Guillermo Ricardo Simari,et al.  An analysis of the computational complexity of DeLP through game semantics , 2005 .

[17]  Jeff Z. Pan,et al.  Inconsistencies, Negations and Changes in Ontologies , 2006, AAAI.

[18]  Pascal Hitzler,et al.  Paraconsistent Reasoning for OWL 2 , 2009, RR.

[19]  Anthony Hunter,et al.  Elements of Argumentation , 2007, ECSQARU.

[20]  Guillermo Ricardo Simari,et al.  Argument-based mixed recommenders and their application to movie suggestion , 2014, Expert Syst. Appl..

[21]  Guillermo Ricardo Simari,et al.  Relational databases as a massive information source for defeasible argumentation , 2013, Knowl. Based Syst..

[22]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[23]  Riccardo Rosati,et al.  Tractable Approximations of Consistent Query Answering for Robust Ontology-based Data Access , 2013, IJCAI.

[24]  Guilin Qi,et al.  Measuring Incoherence in Description Logic-Based Ontologies , 2007, ISWC/ASWC.

[25]  Jeff Z. Pan,et al.  An Argument-Based Approach to Using Multiple Ontologies , 2009, SUM.

[26]  Jan Chomicki,et al.  Consistent Query Answering: Five Easy Pieces , 2007, ICDT.

[27]  James P. Delgrande,et al.  Parallel belief revision: Revising by sets of formulas , 2012, Artif. Intell..

[28]  Guillermo Ricardo Simari,et al.  A Mathematical Treatment of Defeasible Reasoning and its Implementation , 1992, Artif. Intell..

[29]  Guillermo Ricardo Simari,et al.  On the Use of Presumptions in Structured Defeasible Reasoning , 2012, COMMA.

[30]  Matthias Thimm,et al.  Realizing Argumentation in Multi-agent Systems Using Defeasible Logic Programming , 2009, ArgMAS.

[31]  Meghyn Bienvenu,et al.  On the Complexity of Consistent Query Answering in the Presence of Simple Ontologies , 2012, AAAI.

[32]  Thomas Lukasiewicz,et al.  Inconsistency Handling in Datalog+/- Ontologies , 2012, ECAI.

[33]  Jan Chomicki,et al.  Consistent query answers in inconsistent databases , 1999, PODS '99.

[34]  Michael Wooldridge,et al.  On the Complexity of Linking Deductive and Abstract Argument Systems , 2006, AAAI.

[35]  Stefan Woltran,et al.  Complexity of semi-stable and stage semantics in argumentation frameworks , 2010, Inf. Process. Lett..

[36]  Frank van Harmelen,et al.  Reasoning with Inconsistent Ontologies , 2005, IJCAI.

[37]  Madalina Croitoru,et al.  What Can Argumentation Do for Inconsistent Ontology Query Answering? , 2013, SUM.

[38]  Stefan Woltran,et al.  Merging Logic Programs under Answer Set Semantics , 2009, ICLP.

[39]  Andrea Calì,et al.  A general Datalog-based framework for tractable query answering over ontologies , 2012, J. Web Semant..