Transitive Roles in Number Restrictions Yevgeny Kazakov, Ulrike Sattler, Evgeny Zolin The University of Manchester

Slides:



Advertisements
Similar presentations
Upper Ontology Summit March 14, 2006 Michael Gruninger Semantic Technologies Laboratory University of Toronto.
Advertisements

Doc.: IEEE /082r0 Submission January 2001 Anuj Batra et al., Texas InstrumentsSlide 1 Project: IEEE P Working Group for Wireless Personal.
Charting the Potential of Description Logic for the Generation of Referring Expression SELLC, Guangzhou, Dec Yuan Ren, Kees van Deemter and Jeff.
Completeness and Expressiveness
SOTIRIS BATSAKIS EURIPIDES G.M. PETRAKIS TECHNICAL UNIVERSITY OF CRETE INTELLIGENT SYSTEMS LABORATORY Imposing Restrictions Over Temporal Properties in.
Query Answering based on Standard and Extended Modal Logic Evgeny Zolin The University of Manchester
Modal Logic with Variable Modalities & its Applications to Querying Knowledge Bases Evgeny Zolin The University of Manchester
CS848: Topics in Databases: Foundations of Query Optimization Topics covered  Introduction to description logic: Single column QL  The ALC family of.
Knowledge Representation and Reasoning using Description Logic Presenter Shamima Mithun.
ARCHITECTURES FOR ARTIFICIAL INTELLIGENCE SYSTEMS
Query Answering for OWL-DL with Rules Boris Motik Ulrike Sattler Rudi Studer.
Comparative Succinctness of KR Formalisms Paolo Liberatore.
TReasoner: System Description Andrei Grigorev Postgraduate student Tyumen State University.
1 A Description Logic with Concrete Domains CS848 presentation Presenter: Yongjuan Zou.
Undecidability of the Membership Problem for a Diagonal Matrix in a Matrix Semigroup* Paul Bell University of Liverpool *Joint work with I.Potapov.
Combining the strengths of UMIST and The Victoria University of Manchester A Tableaux Decision Procedure for SHOIQ Ian Horrocks and Ulrike Sattler University.
January 5, 2015CS21 Lecture 11 CS21 Decidability and Tractability Lecture 1 January 5, 2015.
1 Introduction to Computability Theory Lecture15: Reductions Prof. Amos Israeli.
1 Introduction to Computability Theory Lecture12: Reductions Prof. Amos Israeli.
CPSC 322, Lecture 23Slide 1 Logic: TD as search, Datalog (variables) Computer Science cpsc322, Lecture 23 (Textbook Chpt 5.2 & some basic concepts from.
The Theory of NP-Completeness
Description Logics. Outline Knowledge Representation Knowledge Representation Ontology Language Ontology Language Description Logics Description Logics.
The Complexity of Adding Failsafe Fault-tolerance Sandeep S. Kulkarni Ali Ebnenasir.
Gradient Methods Yaron Lipman May Preview Background Steepest Descent Conjugate Gradient.
Normal forms for Context-Free Grammars
Reducing OWL Entailment to Description Logic Satisfiability Ian Horrocks and Patel Schneider Presented by: Muhammed Al-Muhammed.
Abstract Verification is traditionally done by determining the truth of a temporal formula (the specification) with respect to a timed transition system.
Part 6: Description Logics. Languages for Ontologies In early days of Artificial Intelligence, ontologies were represented resorting to non-logic-based.
Geometric Probing with Light Beacons on Multiple Mobile Robots Sarah Bergbreiter CS287 Project Presentation May 1, 2002.
2-5 Postulates Ms. Andrejko.
Evgeny Zolin, School of Computer Science, University of Manchester, UK, Andrey Bovykin, Department of Computer Science, University.
Deciding a Combination of Theories - Decision Procedure - Changki pswlab Combination of Theories Daniel Kroening, Ofer Strichman Presented by Changki.
Deciding Semantic Matching of Stateless Services Duncan Hull †, Evgeny Zolin †, Andrey Bovykin ‡, Ian Horrocks †, Ulrike Sattler † and Robert Stevens †
 Copyright 2005 Digital Enterprise Research Institute. All rights reserved. Towards Translating between XML and WSML based on mappings between.
An Introduction to Description Logics. What Are Description Logics? A family of logic based Knowledge Representation formalisms –Descendants of semantic.
Propositional Resolution Computational LogicLecture 4 Michael Genesereth Spring 2005.
CSE-291: Ontologies in Data & Process Integration Department of Computer Science & Engineering University of California, San Diego CSE-291: Ontologies.
Ming Fang 6/12/2009. Outlines  Classical logics  Introduction to DL  Syntax of DL  Semantics of DL  KR in DL  Reasoning in DL  Applications.
Query Answering Based on the Modal Correspondence Theory Evgeny Zolin University of Manchester Manchester, UK
Benjamin Gamble. What is Time?  Can mean many different things to a computer Dynamic Equation Variable System State 2.
Using the TBox to Optimise SPARQL Queries Birte Glimm Yevgeny Kazakov Ilianna Kollia and Giorgos Stamou CS 848 Paper Critique Vishnu Prathish.
- r r Saturation-Based Decision Procedures and Complexity Analysis Yevgeny Kazakov R. 615 Applications Add semantic markup to a.
DRAGO: Distributed Reasoning Architecture for the Semantic Web Andrei Tamilin and Luciano Serafini Work is supported by 1 June 2005 Second European Semantic.
An Introduction to Description Logics (chapter 2 of DLHB)
CS 345: Chapter 8 Noncomputability and Undecidability Or Sometimes You Can’t Get It Done At All.
Course Overview and Road Map Computability and Logic.
Slide #3-1 Chapter 3: Foundational Results Overview Harrison-Ruzzo-Ullman result –Corollaries.
CSCI 3160 Design and Analysis of Algorithms Tutorial 10 Chengyu Lin.
1 How to decide Query Containment under Constraints using a Description Logic Ian Horrocks, Ulrike Sattler, Sergio Tessaris, and Stephan Tobies presented.
More on Description Logic(s) Frederick Maier. Note Added 10/27/03 So, there are a few errors that will be obvious to some: So, there are a few errors.
CS6133 Software Specification and Verification
Lecture 5 1 CSP tools for verification of Sec Prot Overview of the lecture The Casper interface Refinement checking and FDR Model checking Theorem proving.
A Preferential Tableau for Circumscriptive ALCO RR 2009 Stephan Grimm Pascal Hitzler.
Daniel Kroening and Ofer Strichman Decision Procedures An Algorithmic Point of View Deciding Combined Theories.
Using Redundancy and Basicness for Obtaining Decision Procedures for Fragments of FO-logic December, 2003AG-2 Logic Seminar, Schloß Ringberg1 Using.
Complexity of Reasoning
Hitzler ● OWL1.1 Rules ● DedSys Saarbrücken ● March 2008 AIFB ReaSem Slide 1 OWL 1.1 Rules Markus Krötzsch Sebastian Rudolph Pascal Hitzler AIFB, University.
Using OWL 2 For Product Modeling David Leal Caesar Systems April 2009 Henson Graves Lockheed Martin Aeronautics.
Disjunctive Bottom Set and Their Computation Dr Wenjin Lu & Dr Ross King Department of Computer Science, The University of Wales, Aberystwyth
2.5 Postulates and Proofs GEOMETRY. Postulate (axiom)- a statement that is accepted as true without proof 2.1: Through any two points, there is exactly.
Slide 1 of 24 VIII MUTATIONS Mutations Types of Mutations:
End Show Slide 1 of 24 Copyright Pearson Prentice Hall 12-4 Mutations Outline 12–4: Mutations.
On Abductive Equivalence Katsumi Inoue National Institute of Informatics Chiaki Sakama Wakayama University MBR
Lecture 9: Query Complexity Tuesday, January 30, 2001.
1 Representing and Reasoning on XML Documents: A Description Logic Approach D. Calvanese, G. D. Giacomo, M. Lenzerini Presented by Daisy Yutao Guo University.
Jie Bao, Doina Caragea and Vasant G Honavar
Proficiency Level Definitions
Chapter 10: Mathematical proofs
Ontology.
Ontology.
Presentation transcript:

Transitive Roles in Number Restrictions Yevgeny Kazakov, Ulrike Sattler, Evgeny Zolin The University of Manchester

Talk Outline Motivating examples Definitions: where the problem lies Solution: to give a good definition Main results: (Un)decidability Open problems: towards a criterion

Motivating examples A human has 2 hands, each with 5 fingers: Human v 6 2 hasPart.Hand Hand v 6 5 hasPart.HandFinger Then the concept Human u ( > 11 hasPart.HandFinger) is unsatisfiable, provoded (!) that hasPart is transitive A symphony consists of (at most) 4 movements Symphony v MusicalComposition u ( 6 4 hasPart.Movement ) A quartet consists of exactly 4 instruments Quartet v ( 6 4 hasPart. Instrument ) u ( > 4 hasPart. Instrument ) …any other ontologies involving partonomy

… more examples Lists are modeled in ontolodies using two roles: hasNext— to link elements in a chain isFollowedBy— to jump in few steps in a chain Axioms: hasNext v isFollowedBy, Trans(isFollowedBy ) A list has at most 1 ending element: List v ( 6 1 isFollowedBy. :9 hasNext. > ) A protein sequence D contains 5 amino-acids of type B ProtSeqD v ( > 5 isFollowedBy. AminoAcidB )

What’s in the SHIQ ? Syntax for concepts of the Description Logic SHIQ : Syntax for knowledge base:

The problem and the usual remedy Theorem. The following problem is undecidable: given R, T, C  satisfiable? (Yes/No) Patch: Then we regain decidability!... At the cost of loss of expressivity...

Safety of an RBox Theorem. The following problem is undecidable: given R 0, T, C  satisfiable? (Yes/No) where R 0 = Star 4 (even without inverses!) We call Star 4 unsafe for ALCQ Q1. Which RBoxes are safe? (with or without inverses) Can we decide whether an RBox is safe? Q2. For safe RBoxes, what is the decision problem for satisfiability? Complexity? Algorithms? Implementation? transitive non-transitive

Main results. Good news: Decidability Theorem 3 (without inverses). An RBox is safe, if for any transitive roles R and S, either R v S or S v R. Corollary: { } and { } are safe! All examples from the first slides are decidable. Moreover: Theorem 4 (Modularity). If two RBoxes R 1 and R 2 are safe and do not share any roles, then R 1 [ R 2 is safe.

Main results. Bad news: Undecidability Theorem 1 ( with inverses ). The following RBox is unsafe: R = { Trans ( R ) } So, is the hope for decidability lost? Conjecture. If we use number restrictions on R, but not on R –, i.e.: ( ? nR. C ), but not ( ? nR –. C ), then it is safe. Theorem 2 ( without inverses ). These RBoxes are unsafe: ? Not yet:

Towards a criterion of safety Theorem 5 ( without inverses ). These RBoxes are unsafe: and any their extensions. Conjecture (Criterion): No other unsafe RBoxes exist! min! RS Q A little nuance: Q = min ( R, S )

Conclusions and future directions Borderline between safety and unsafety – almost done A smarter notion of a simple role in SHIQ – to be found “Semi-simple role”: number restrictions are allowed for the role, but not for the inverse – no results at all so far Complexity Practical algorithms Implementations …

The roads we take… The grids we tile… Thank you!