International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Task-Based Ontology of Problem Solving Adapters for Developing Intelligent Systems

  • Ko, Jesuk (Department of Industrial and Information Engineering Gwangju University) ;
  • Kitjongthawonkul, Somkiat (School of Business & Informatics Australian Catholic University)
  • Published : 2004.12.01
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Abstract

In this paper we describe Task-Based Problem Solving Adapters (TPSAs) for modeling a humam solution (through activity-centered analysis) to a software solution (in form of computer-based artifact). TPSAs are derived from the problem solving pattern or consistent problem solving structures/strategies employed by practitioners while designing solutions to complex problems. The adapters developed by us lead toward human-centeredness in their design and underpinning that help us to address the pragmatic task constraints through a range of technologies like neural networks, fuzzy logic, and genetic algorithms. We also outline an example of applying the TPSAs to develop a working system for assisting sales engineers of an electrical manufacturing firm in preparing indent and monitoring the status of orders in the company.

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References

  1. B. Chandrasekaran, T. R. Johnson and J. W. Smith, 'Taskstructure analysis for knowledge modeling,' Communications of the ACM, Vol. 35, pp. 124-136, 1992 https://doi.org/10.1145/130994.131002
  2. L. Steels, 'Components of expertise,' AI Magazine, Vol. 11, pp. 28-49, 1990
  3. A. T. Schreiber, B. J. Wielinga and J. A. Breuker, KADS: A Principle Approach to KnowledgeBased System Development, Acade:nic Press, London, 1993
  4. G. Schreiber, B. Wielinga, R. de Hoog, H. Akkermans and W. V. de Velde, 'CommonKADS: A comprehensivemethodology for KBS development,' IEEE Expert, pp. 28-37, 1994
  5. J. Angele, D. Fensel, D. Landes and R. Studer, 'Developing knowledge-based systems with MIKE,' Journal of Automated Software Engineering, Vol. 5, pp.389-418, 1998 https://doi.org/10.1023/A:1008653328901
  6. D. Fensel and R. Groenboom, A software architecture for knowledge-based systems, http://www.cs.vu.nl/-dieter/ publications, (Current 10 May 2004)
  7. E. Gamma, R. Helm, R. Johnson and J. Vlissides, Design Patterns, Addison-Wesley Publication, 1995
  8. D. Fensel and R. Groenboom, 'Specifying knowledgebased systems with reusable components,' In Proceedings of the 9th International Conference on Software Engineering & Knowledge Engineering (SEKE-97), Madrid, Spain, 1997
  9. J. Zhang and D. A. Norman, 'Representations in distributed cognitive tasks,' Cognitive Science, Vol. 18, pp. 87-112, 1994 https://doi.org/10.1016/0364-0213(94)90021-3
  10. R. Khosla and T. Dillon, Engineering Intelligent Hybrid Multi-Agent Systems, Kluwer Academic Publishers, 1997
  11. R. Khosla and T. Dillon, 'Cognitive and computational foundations of symbolic-connectionist integration,' In ECAI'94 Workshop Proceedings on SymbolicConnectionist Processing, Netherlands, Holland, 1994
  12. R. Khosla and T. Dillon, 'Perspectives for integration of artificial neural networks and expert systems,' In IEEE Australia-New Zealand Conference on Information Systems, Perth, Australia, 1993, pp. 624-628
  13. B. Chandrasekaran, J. R. Josephson and V. R. Benjamins, 'Ontology of tasks and methods,' http://www.cis. ohiostate.edul-chandralpub, (Current 10 May 2004)