3 ont reasoning

8/6/2019 3 Ont Reasoning

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Joost Breuker

Leibniz Center for LawUniversity ofAmsterdam

Ontology, ontologies and ontologicalreasoning3: ontological reasoning


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Overview

Semantic Web and OWL Use of ontologies

Reasoning with ontologies TRACS: testing the Dutch Traffic Regulation

HARNESS: DL-based legal assessment

Frameworks and the limits of DL basedreasoning

Problem solving and reasoning


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What the Semantic Web is intended for

Dream part 2

In communicating between people using the Web, computersand networks have as their job to enable the informationspace, and otherwise get out of their way. But doesnt it

make sense to also bring computers more onto action, toput their analytic power to work. In part two of thedream, that is just what they do. The first step is puttingdata on the web in a form that machines can naturallyunderstand, or converting it to that form. This createswhat I call a Semantic Web -- a web of data that can be

processed directly or indirectly by machines. [p191]


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A decade later (W3C): infrastructural standards for SW

Semantics are represented by ontologies Ontologies are represented by a KR formalism

Note: ontologies were specifications in KE (usingOntolingua; CML, cf UML in SE)

On top of a layer cake of data-handling formalisms

KR formalism is intended for reasoning Even suitable for blind trust (OWL-DL is decidable)


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Legal ontologies (from Nuria Casellas, 2008/9)


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HOWEVER, in practice

Not one of these ontologies is used forreasoning

Use: Information management (documents)

That is also what the current Semantic Web efforts areabout (not only in legal domains)

Core ontologies (reuse?)

Why using OWL?


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OWL: DL-based knowledge representation

OWL-DL is a unique result of 40 years ofresearch in AI about KR

Semantic networks, KL-ONE, CLASSIC, LOOM,.. Concept oriented representation

Very suitable for ontologies

vs Rule based KR

End 80-ies: logical foundations A KR formalism defines what can be correctly and

completely inferred On the basis of the semantics (model theory) of the

formalism

Problem: finding a sub-set of predicate logic that is

decidable (and computationally tractable)


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OWLs further requirements/problems

besides the expressivity/decidability trade-off The RDF layer (OO based) was a serious

obstacle Its expressiveness was incompatible with DL research

Ian Horrocks, Peter F. Patel-Schneider, and Frank van Harmelen.From SHIQand RDF to OWL: The making of a web ontologylanguage. Journal of Web Semantics, pages 726, 2003.

No unique naming assumption

USA/EU team: KR & KA community NB: improved expressivity in OWL 2!

Still: OWL is not a self-evident for novices


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Reasoning with OWL

Main inference: classification on the basis ofproperties of concepts Reasoner (inference engine) `classifier

Complete for DL based

Rule based reasoners are not complete Eg Prolog, unless `closed world assumption

For the Web this assumption cannot hold!

T(erminolgy)-Box: ontology (knowledge)

Classes (concepts, universals) and properties(relations, attributes, features,..)

A(ssertions)-Box: some situation (information) Individuals (instances) with properties


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When is REASONING with ontologies indicated

(...except for consistency checking etc.) In understanding/modeling situations

Situation = events and states of entities in space(and over time)

Two main modes Text understanding (stories, cases)

Nb exc. expository discourse

Scene understanding (robotics)


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When is REASONING with ontologies required

When all possible situations have to be modeled Typical examples:

Model based & qualitative reasoning systems

Testing system models

..legal case assessment

All possible combinations completeness &consistency eg OWL-DL

NB: in knowledge systems, situations are usually

modeled implicitly in user-system dialogues: Asking user (values of/presence of) parameters

Heuristics; human limitations in handlingcombinatorics


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For instance: TRACS (1990 1994)

Testing a new Dutch traffic code (RVV-90) art. 3 Vehicles should keep to the right

art. 6 Two bicycles may ride next to each other

art. 33 A trailer should have lights at the back

Questions Consistent?

Complete?

In what respect different from RVV-66 (old one)?

These can only be answered when we canmodel all possible situations distinguished bythis code


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Traffic participants: a part of the ontology (`world knowledge)

traffic-participant

pedestrian driver

bicyclist autocyclistdriver ofmotor vehicle

car driver motorcycledriverlorry driverbus driver


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Simple example of ontological reasoning

Ontology (T-Box) Subsumes (Physical_object, Car)

Right-of (Physical_object, Physical_object)

Inv(Right_of, Left_of)

ase description (A-Box)

Is-a (car1, Car)

Is-a (car1, Car)

Right_of (car1, car2)

lassifier(eg Pellet)

Left_of (car2, car1) (A-Box)

simple as that, but necessary


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Architecture of TRACS (Breuker & den Haan, 94)

WORLDKNOWLEDGEBASE

META-LEGALKNOWLEDGEBASE

REGULATIONKNOWLEDGEBASE

REGULATIONAPPLIER

CONFLICTRESOLVER

SITUATIONGENERATOR

SITUATION

APPLICABLERULES

TRESPASSED/NON-TRESPASSEDRULES

CONSISTENTLYAPPLICABLERULES

VALIDATOR


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Btw: some surprising results

Tram on

tramway

Car on bicycle

lane


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Just a prototype

About 105 possible combinations Analysis of redundancy (symmetry)

Still: too many for humans to inspect!

But:

Differences with old regulation Differences with foreign regulations ( ontology the same?)

political decisions


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HARNESS: OWL 2 DL also for normative reasoning

Normative reasoning simultaneously withontological reasoning using OWL-DL

Estrella, 6th framework, 2006-2008 http://www.estrellaproject.org/

Saskia van de Ven, Joost Breuker, Rinke Hoekstra, Lars Wortel, and Abdallah El-Ali.Automated legal assessment in OWL 2. In Legal Knowledge and InformationSystems. Jurix 2008: The 21st Annual Conference, Frontiers in Artificial Intelligence

and Applications. IOS Press, December 2008.

Andrs Frhcz and Gyrgy Strausz, Legal Assessment Using Conjunctive Queries,Proceedings LOAIT 2009


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Representing norms in OWL DL 2

Norm Generic case description is a conjunction of generic

situation () descriptions

Generic case description is a class (7)

A deontic qualification (P,O,F) is associated with 7

Case description is an individual (C)

Description is itself composed of classes/individuals

as defined in the ontology!


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Watch this.


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What did you see?

Event 1 (Saskia entering, shows ID) Event 2 (Joost entering, shows ID)

Event 3 (Radboud entering)

(nb : Radboud is president of Jurix)


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JURIX 2009 Regulation

1. For entering a U-building, identification isrequired

2. The President does not need an identification toenter a U-building


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Generic situations and generic case

1. For (entering a U-building), (an identification) isrequired

2. The (President) does not need (anidentification) to (enter a U-building)

Step 1: Modeled as:

(1) 1 | 123

(1) 2 | 42(~3)


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Generic situations and generic case

1. For (entering a U-building), (an identification) isrequired [for each person]

2. The (President) does not need (anidentification) to (enter a U-building)

Step 1: Modeled as:

(1) 1 | 123

(1) 2 | 42(~3)


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Step 2: Adding deontic qualification to the norms

Permitted(1) | 123(1) Obliged(1)

Forbidden(1)| 12(~3)

(this is a `design pattern which separatesconditions (person, entering and identityfroma forbidden generic case)

(2) Permitted(2)| 42(~3)

President


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Step 3 Normative assessment: classifying C(ase)

Case: President Radboud enters U-building C: {s4,s2}

Classifying C:

1 subsumes 2 exception

C is Disallowed-by 1 C is Allowed-by 2 Etc, etc

This is not viewed as a logical conflict byPellet due to

the fact that this individual is classified by two

different norms (classes)

HARNESS selects subsumed (2)


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Experimental user interface (Protg plug-in)

ViolationCompliance


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An important advantage

Three knowledge bases: domain ontology (T-Box)

norms (T-Box)

case description (individuals & properties; A-Box)

OWL-DL reasoner (Pellet) `classifies case interms of concepts and of norms simultaneouslyin an intertwined fashion

Hybrid or only-rule-based solutions cannotpreserve all (inferred) information of theontology as Pellet/OWL 2 does


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Whats further new

Monotonic and deductive: Unique & against accepted wisdom

Exceptions do not lead to conflict

Advantage:

Reasoning is sound and complete (trust) No rule formalism allows this with the same expressiveness

Full use of OWL 2 DLs expressiveness

No loss in translation

Disadvantage: Modeling in DL is found to be more intellectually

demanding than modeling in rules anyway Obligation design pattern is not very intuitive


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A serious problem in the use of (OWL-) DL

DL representations are `variable free (most) rule formalisms have variables

Moreover: in OWL names of individuals are nottaken as identifiers of individuals (no unique

naming assumption) It is not possible to track changes of a particular

individual

A-Box: colour(block1,red); colour(block1,blue)

OWL: there are (now) two block1s!


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A serious problem in the use of (OWL-) DL (2)

Also: it is (almost) impossible to `enforceidentity of individuals in OWL

Example: transaction


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OWLs restriction on the form of graphs

`diamond of individuals

what OWL allows: trees


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An approximate solution: a special design pattern

Constraining the identity:

Rinke Hoekstra and Joost Breuker. Polishing diamonds in OWL2. In Aldo Gangemi and Jrme Euzenat,editors, Proceedings of the 16th International Conference on Knowledge Engineering andKnowledge Management (EKAW 2008), LNAI/LNCS. Springer Verlag, October 2008.)

Rinke Hoekstra. OntologyRepresentation - Design Patterns andOntologies that Make Sense, volume

197 of Frontiers of Artificial Intelligence and Applications. IOS Press, Amsterdam, June 2009.


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The DL view has a limited scope

Excellent for axiomatic grounding of the termsthat form the lowest level of granularity of aknowledge base

More complex knowledge structures

(frameworks) will require also rules `Hybrid solution:In the hybrid approach there is a strict separation between the

ordinary predicates, which are basic rule predicates and ontology

predicates, which are only used as constraints in rule antecedents.Reasoning is done by interfacing an existing rule reasoner with anexisting ontology reasoner

Problem: rule formalism has to be `DL-safe OWL/rule combination still (W3C) research issue


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Frameworks

3 ont reasoning

Documents