Browse > Article
http://dx.doi.org/10.5391/IJFIS.2004.4.3.353

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)
Publication Information
International Journal of Fuzzy Logic and Intelligent Systems / v.4, no.3, 2004 , pp. 353-360 More about this Journal
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.
Keywords
Task-Based Ontology; Problem Solving Adapters; Intelligent Systems; Human-Centeredness;
Citations & Related Records
연도 인용수 순위
  • Reference
1 D. Fensel and R. Groenboom, A software architecture for knowledge-based systems, http://www.cs.vu.nl/-dieter/ publications, (Current 10 May 2004)
2 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   DOI   ScienceOn
3 R. Khosla and T. Dillon, Engineering Intelligent Hybrid Multi-Agent Systems, Kluwer Academic Publishers, 1997
4 L. Steels, 'Components of expertise,' AI Magazine, Vol. 11, pp. 28-49, 1990
5 B. Chandrasekaran, J. R. Josephson and V. R. Benjamins, 'Ontology of tasks and methods,' http://www.cis. ohiostate.edul-chandralpub, (Current 10 May 2004)
6 J. Zhang and D. A. Norman, 'Representations in distributed cognitive tasks,' Cognitive Science, Vol. 18, pp. 87-112, 1994   DOI   ScienceOn
7 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
8 A. T. Schreiber, B. J. Wielinga and J. A. Breuker, KADS: A Principle Approach to KnowledgeBased System Development, Acade:nic Press, London, 1993
9 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
10 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
11 E. Gamma, R. Helm, R. Johnson and J. Vlissides, Design Patterns, Addison-Wesley Publication, 1995
12 B. Chandrasekaran, T. R. Johnson and J. W. Smith, 'Taskstructure analysis for knowledge modeling,' Communications of the ACM, Vol. 35, pp. 124-136, 1992   DOI
13 R. Khosla and T. Dillon, 'Cognitive and computational foundations of symbolic-connectionist integration,' In ECAI'94 Workshop Proceedings on SymbolicConnectionist Processing, Netherlands, Holland, 1994