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An Ontology-Based Functional Modeling Approach for Multi-agent Distributed Design on the Semantic Web

  • Wenyu Zhang
  • Lanfen Lin
  • Jiong Qiu
  • Ruofeng Tong
  • Jinxiang Dong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3865)

Abstract

This paper describes a preliminary attempt at using Semantic Web paradigm, especially the Web Ontology Language (OWL), for functional design knowledge representation during functional modeling in a multi-agent distributed design environment. An ontology-based functional modeling framework is proposed as a prelude to a meaningful agent communication for collaborative functional modeling. Formal knowledge representation in OWL format extends traditional functional modeling with capabilities of knowledge sharing and distributed problem solving, and is used as a content language within the FIPA ACL (Agent Communication Language) messages in a proposed multi-agent architecture. The ontological enhancement to functional modeling facilitates the implementation of Computer Supported Cooperative Work (CSCW) in functional design for Semantic Web applications.

Keywords

Resource Description Framework Description Logic Functional Modeling Functional Design Computer Support Cooperative Work 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Tor, S.B., Britton, G.A., Chandrashekar, M., Ng, K.W.: Functional Design. In: Usher, J., Roy, U., Parsaei, H. (eds.) Integrated Product and Process Development: Methods, Tools and Technologies, pp. 29–58. John Wiley & Sons, New York (1998)Google Scholar
  2. 2.
    Labrou, Y., Finin, T., Peng, Y.: Agent Communication Languages: The Current Landscape. IEEE Intelligent Systems and Their Applications 14, 45–52 (1999)CrossRefGoogle Scholar
  3. 3.
    Foundation for Intelligent Physical Agents: FIPA Specifications (2002), http://www.fipa.org/specifications/
  4. 4.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284, 34–43 (2001)CrossRefGoogle Scholar
  5. 5.
    McGuinness, D.L., Harmelen, F.V.: OWL Web Ontology Language Overview (March 20, 2004), http://www.w3.org/TR/2004/REC-owl-features-20040210/
  6. 6.
    Bellifemine, F., Poggi, A., Rimassa, G.: Developing Multi Agent Systems with a FIPACompliant Agent Framework. Software Practice & Experience 31, 103–128 (2001)CrossRefzbMATHGoogle Scholar
  7. 7.
    Umeda, Y., Ishii, M., Yoshioka, M., et al.: Supporting Conceptual Design Based on the Function-Behavior-State Modeler. Artificial Intelligence for Engineering Design, Analysis and Manufacturing: Aiedam 10, 275–288 (1996)CrossRefGoogle Scholar
  8. 8.
    Goel, A.: Model Revision: A Theory of Incremental Model Learning. In: Proceedings of the 8th International Conference on Machine Learning, pp. 605–609 (1991)Google Scholar
  9. 9.
    Qian, L., Gero, J.S.: Function-Behavior-Structure Paths and Their Role in Analogy-Based Design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10, 289–312 (1996)CrossRefGoogle Scholar
  10. 10.
    Prabhakar, S., Goel, A.: Functional Modeling for Enabling Adaptive Design of Devices for New Environments. Artificial Intelligence in Engineering 12, 417–444 (1998)CrossRefGoogle Scholar
  11. 11.
    Deng, Y.-M., Tor, S.B., Britton, G.A.: Abstracting and Exploring Functional Design Information for Conceptual Product Design. Engineering with Computers 16, 36–52 (2000)CrossRefGoogle Scholar
  12. 12.
    Zhang, W.Y., Tor, S.B., Britton, G.A.: A Graph and Matrix Representation Scheme for Functional Design of Mechanical Products. International Journal of Advanced Manufacturing Technology 25, 221–232 (2005)CrossRefGoogle Scholar
  13. 13.
    Szykman, S., Senfaute, J., Sriram, R.D.: The Use of XML for Describing Functions and Taxonomies in Computer-Based Design. In: Proceedings of the ASME Computers and Information in Engineering Conference, DETC99/CIE-9025, Las Vegas, NV (1999)Google Scholar
  14. 14.
    Bohm, M.R., Stone, R.B., Szykman, S.: Enhancing Virtual Product Representations for Advanced Design Repository Systems. In: Proceedings of the ASME Computers and Information in Engineering Conference, DETC2003/CIE-48239, Chicago, IL (2003)Google Scholar
  15. 15.
    Saaksvuori, A., Immonen, A.: Product Lifecycle Management. Springer, Heidelberg (2003)Google Scholar
  16. 16.
    Kitamura, Y., Mizoguchi, R.: Ontology-Based Description of Functional Design Knowledge and Its Use in a Functional Way Server. Expert Systems with Applications 24, 153–166 (2003)CrossRefGoogle Scholar
  17. 17.
    Mizoguchi, R., Kitamura, Y.: Foundation of Knowledge Systematization: Role of Ontological Engineering. In: Roy, R. (ed.) Industrial Knowledge Management – A Micro Level Approach, pp. 17–36. Springer, London (2000)Google Scholar
  18. 18.
    World Wide Web Consortium (W3C) (2004), http://www.w3.org
  19. 19.
    Felfernig, A., Friedrich, G., Jannach, D., et al.: Configuration Knowledge Representations for Semantic Web Applications. Artificial Intelligence for Engineering Design, Analysis and Manufacturing: Aiedam 17, 31–50 (2003)CrossRefGoogle Scholar
  20. 20.
    Gruber, T.R.: A Translation Approach to Portable Ontology Specification. Knowledge Acquisition 5, 190–220 (1993)CrossRefGoogle Scholar
  21. 21.
    Fikes, R., Hayes, P., Horrocks, I.: OWL-QL – A Language for Deductive Query Answering on the Semantic Web. In: Knowledge Systems Laboratory, Stanford University, Stanford, CA (2003)Google Scholar
  22. 22.
    Horrocks, I., Sattler, U., Tobies, S.: Practical Reasoning for Expressive Description Logics. In: Ganzinger, H., McAllester, D., Voronkov, A. (eds.) LPAR 1999. LNCS, vol. 1705, pp. 161–180. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  23. 23.
    Haarslev, V., Moller, R.: Racer: A Core Inference Engine for the Semantic Web. In: Proceedings of the 2nd International Workshop on Evaluation of Ontology-Based Tools, pp. 27–36 (2003)Google Scholar
  24. 24.
    Gennari, J.H., Musen, M.A., Fergerson, R.W., et al.: The Evolution of Protégé-2000: An Environment for Knowledge-Based Systems Development. International Journal of Human-Computer Studies 58, 89–123 (2003)CrossRefGoogle Scholar
  25. 25.
    Knublauch, H., Musen, M.A., Rector, A.L.: Editing Description Logics Ontologies with the Protégé OWL Plugin. In: International Workshop on Description Logics, Whistler, BC, Canada (2004)Google Scholar
  26. 26.
    Rriedman-Hill, E.J.: Jess, the Expert System Shell for the Java Platform (2002), http://herzberg.ca.sandia.gov/jess

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wenyu Zhang
    • 1
  • Lanfen Lin
    • 2
  • Jiong Qiu
    • 2
  • Ruofeng Tong
    • 2
  • Jinxiang Dong
    • 2
  1. 1.College of InformationZhejiang University of Finance & EconomicsHangzhouChina
  2. 2.Institute of Artificial IntelligenceZhejiang UniversityHangzhouChina

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