practical goal-based reasoning in ontology-driven applications huy pham & deborah stacey school...
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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
Knowledge Engineering and Ontology Development 2011
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Illustrative Example
Knowledge Engineering and Ontology Development 2011
• (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