Practical Goal-based Reasoning in Ontology-Driven Applications Huy Pham & Deborah Stacey School of Computer Science University of Guelph Guelph, Ontario,

Practical Goal-based Reasoning in Ontology-Driven Applications

Huy Pham & Deborah Stacey

School of Computer ScienceUniversity of Guelph

Guelph, Ontario, Canada

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Quick Overview

• A more practical way to do planning in ontology-driven applications

• Some interesting challenges, and some (hopefully) interesting ideas

• Result: A reusable integration framework for bringing planning into onto-driven apps

Knowledge Engineering and Ontology Development 2011

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Motivation

• Today's intelligent systems are knowledge-intensive

• And would benefit from an onto-driven approach• Standardized semantics Reusable

• KB built for one app is understood by many others• Expressive Rich models• Reasoning services Modular models

• Problem: Inadequate reasoning support

Knowledge Engineering and Ontology Development 2011

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Onto Reasoning vs Goal-based Reasoning

• Reasoning about structure vs reasoning about actions

“Is this class a subclass of that class?”vs

“Is there a way to get to the goal state?”

• Static vs Dynamic

• Tableaux (DL, Open-world) vs Resolution (LP, Closed-world)

Knowledge Engineering and Ontology Development 2011

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Existing Approaches

Language-based Approaches

• Idea:• Modify/Extend/Restrict DL to provide rule-based support• SWRL, DLP, etc.

• Very challenging• Theoretical: Decidability, Boundary, etc.• Practical: Tooling support, User acceptance, etc.

• Awaiting more case studies

Knowledge Engineering and Ontology Development 2011

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Existing Approaches

Parallel Modeling Approaches

Idea• Model application knowledge in ontologies• Model planning-related knowledge in a planning language• Have planning programs query the ontologies at runtime

Challenges• KBs in two languages

• System developers have to be well-versed in both• Integration is more likely to be app-specific

Knowledge Engineering and Ontology Development 2011

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How about?

A translation approach

• Model planning-related knowledge in ontology (alongside with other app knowledge)

• Have it translated it into executable rule-based programs (under the hood)

Knowledge Engineering and Ontology Development 2011

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Crazy Ideas?

• Perhaps!

• But planning KBs are now ontology-based• Universally understood/reusable by other apps• Smaller risk of being “stuck” in a non-mainstream language• Make use of existing and mature tool and frameworks• Total independence from the underlying planning framework

• Also, user does not need to learn/worry about the underlying planning formalism

• Partially investigated by Rajpathak et al and Gil et al

Knowledge Engineering and Ontology Development 2011

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Two interesting challenges

• Representability• Can we describe planning problems

in ontology?• HL is not a proper subset of HL• Closed world vs open world

• Translatability• How can we ensure the user does

not produce non-translatable problem descriptions?• DL is also a non-proper subset of DL

Knowledge Engineering and Ontology Development 2011

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Observation 1

DL can describe rules (given a proper set of ontologicalconstructs) Triangle(x,y,z) ←

Point(x) Ʌ Point(y) Ʌ Point(z) Ʌ x ≠ y Ʌ y ≠ z Ʌ z ≠ x

can be modeled as:

Knowledge Engineering and Ontology Development 2011

Observation 2

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• An ontology can be viewed as a language• Concepts constitute a vocabulary• Roles dictates how the terms can be combined to form

statements

• As such, we do have some control on what the user can produce• By carefully control the

language constructs in the planning ontology

• In a transparent and non-intrusive ways!

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Proposed Architecture

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Illustrative Example

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• (Simple) Trip Planning• Arrive at UPEC campus from Guelph campus, awake, and

properly rested!• By taking a combination of actions: flights, bus, train, rest,

buy or drink coffee

• Preconditions and Effects

• Planning Heuristics• If at hub airport

• Find direct flight to destination• Find bus or train route to destination • Find flight to another hub airport

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Discussions

• Contributions• An integration framework for bringing planning into Onto-

driven apps• Plus 2 interesting challenges/observations

• What worked?• Demonstrated feasibility with a toy problem• Demonstrated effectiveness with a real-world problem

• What didn't?• Tooling support

• Debugging• Usability

• Language is still a bit technical for an average modeler

Knowledge Engineering and Ontology Development 2011

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Questions and Suggestions

Hope you will read our paper!

More details available at:http://ontology.socs.uoguelph.ca

Thank you!

Knowledge Engineering and Ontology Development 2011