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Using Multi-agent System for Improving and Implementing a New Enterprise Modeling Tool

  • Paul-Eric Dossou
  • Pawel Pawlewski
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 71)

Abstract

GRAI Methodology is one of the three main methodologies for enterprise modeling (with PERA and CIMOSA). To support this methodology different tools are being developed. GRAIXPERT is a hybrid expert system for detecting inconsistencies in enterprises. GRAISUC is a module for choosing and implementing supply chain management tool in enterprises. GRAIQUAL is a module for improving quality system of enterprises. These modules are based on the use of different reasoning (Case-based reasoning (CBR), decomposition, transformation) but also on the enterprise knowledge management. The enterprise knowledge could be explicit or tacit. Each case of enterprise studied allows to improve the knowledge of the tool. Then, Multi-agent systems are used for acquiring this knowledge and managing improvement. This paper presents how Multi-agent system could be associated to CBR and Decomposition reasoning in order to be more efficient during the enterprise modelling.

Keywords

Multi-agent systems Case-Based Reasoning Expert system enterprise modelling performance reference models rules Knowledge 

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References

  1. 1.
    Aamodt, A.: Case-Based Reasoning: foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications 7(1), 39–59 (1994)Google Scholar
  2. 2.
    Burke, E.K., et al.: Structured cases in case-based reasoning – reusing and adapting cases for time-tabling problems. The journal of KBS 13(2-3), 159–165 (2000)Google Scholar
  3. 3.
    Brown, D.C., Chandrasekaran, B.: Expert system for a class of mechanical design activities. In: Knowledge Engineering in CAD. Elsevier, Amsterdam (1985)Google Scholar
  4. 4.
    Dossou, P.E., Mitchell, P.: Using case based reasoning in GRAIXPERT. In: FAIM 2006, Limerick, Ireland (2006)Google Scholar
  5. 5.
    Dossou, P.E., Mitchell, P.: Implication of Reasoning in GRAIXPERT for modeling Enterprises. In: DCAI 2009, Salamanca, Spain (2009)Google Scholar
  6. 6.
    Dossou, P.E., Mitchell, P.: How Quality Management could improve the Supply Chain performance of SMES. In: FAIM 2009, Middlesbrough, United Kingdom (2009)Google Scholar
  7. 7.
    Russell, S.J., Norvig, P.: Artificial Intelligence. A Modern Approach. Prentice-Hall, Englewood Cliffs (1995)zbMATHGoogle Scholar
  8. 8.
    Sen, S., Weiss, G.: Learning in Multiagent Systems. In: Weiss, G. (ed.) Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, ch. 6, pp. 259–298. The MIT Press, Cambridge (1999)Google Scholar
  9. 9.
    Wooldridge, M.: Intelligent Agents. In: Weiss, G. (ed.) Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence, ch. 1, pp. 27–77. The MIT Press, Cambridge (1999)Google Scholar
  10. 10.
    Xia, Q., et al.: Knowledge architecture and system design for intelligent operation support systems. The Journal Expert Systems with Applications 17(2), 115–127 (1999)CrossRefGoogle Scholar
  11. 11.
    Chen, D., Doumeingts, G., Vernadat, F.B.: Architectures for enterprise integration and interoperability. Past, present and future. Computers in Industry 59, 647–659 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Paul-Eric Dossou
    • 1
  • Pawel Pawlewski
    • 2
  1. 1.CAMLa Roche-Sur-YonFrance
  2. 2.Poznan University of TechnologyPoznań

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