Advertisement

A Decision Approach to Select the Best Framework to Treat an IT Problem by Using Multi-Agent System and Expert Systems

  • A. ChakirEmail author
  • M. Chergui
  • S. Elhasnaou
  • H. Medromi
  • A. Sayouti
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 366)

Abstract

This work is registered in two disciplinary axes that are the decision making system, and the practices of the IT GRC. Many organizations deployed integrated the practices of the IT GRC, the problem that arises it is how to choose the good one practices to satisfy a precise need. Our work is motivated by the need to make decisions by understanding and by incorporating perceptions, decisions and actions to make the best choice. The objective of the research is to build a decision-making model to satisfy a precise need IT. The proposed approach bases on three main stages to set up a decision-making model. The model takes in entrance the strategic needs, the first stage consists in reducing the size of the problem by dividing it into many problems, by basing itself on the mapping between all the reference tables and methods of the GRC and also this stage is going to allow us to assure the sequencing of these under problems according to the variables of the environment as for example the type of the organization. In the second stage, it is a question of formalizing every under problems according to the criteria stored in the datawarehouse to generate the best choice of the good practice by using methods of aggregation multi criterion to satisfy the need IT. The third stage consists in estimating the satisfaction IT and helps to make decisions at the level of every chosen reference table.

Keywords

Expert system IT governance Decision method Data warehouse 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Racz, N., Weippl, E., Seufert, A.: A process model for integrated IT governance, risk, and compliance management databases and information systems. In: Proceedings of the Ninth International Baltic Conference, Baltic DB&IS 2010, pp. 155–170. University of Latvia Press, Riga (2010)Google Scholar
  2. 2.
    Kooper, M.N., Maes, R., Roos Lindgreen, E.E.O.: On the governance of information: introducing a new concept of governance to support the management of information. International Journal of Information Management: The Journal for Information Professionals 31(3), 195–200 (2011)CrossRefGoogle Scholar
  3. 3.
    Racz, N., Panitz, J.C., Amberg, M., Weippl, E., Seufert, A.: Governance, risk & compliance (GRC) status quo and software use: results from a survey among large enterprises. In: ACIS 2010 Proceedings, paper 21 (2010). http://aisel.aisnet.org/acis2010/21 (retrieved 13 December 2010)
  4. 4.
    Stachtchenko, P.: COBIT 5, ses apports pour management et la gouvernance du SI, Janvier 25, 2013Google Scholar
  5. 5.
    Delbrayelle, Introduction à ITIL V3 et au cycle de vie des services, juillet 2011. ISO office, Information technology— Security techniques— Code of practice for information security management (2005)Google Scholar
  6. 6.
    ITGI and OGC, Aligning CobiT® 4.1, ITIL® V3 and ISO/IEC 27002 for Business Benefit (2008)Google Scholar
  7. 7.
    Ferber, J.: Les systèmes multi-agents, vers une intelligence collective. InterEditions, 63–144 (1995)Google Scholar
  8. 8.
    Shoham, Y.: Agent-oriented programming. Artificiel Intelligence. Stanford, USA, February 1992Google Scholar
  9. 9.
    Racz, N., Weippl, E., Bonazzi, R.: IT governance, risk & compliance (GRC) status quo and integration. an explorative industry case study. In: Proceedings of the 1st International Workshop on IT GRC, ITGRC 2011. IEEE, Washington (2011)Google Scholar
  10. 10.
    Chakir, A., Medromi, H., Sayouti, A.: La gouvernance du système d’information à base des bonnes pratiques d’ITIL V3. JDTIC, Novembre 2012Google Scholar
  11. 11.
    Chakir, A., Medromi, H., Sayouti, A.: Une approche multi-agents pour la gouvernance d’un data warehouse à base des bonnes pratiques d’ITIL. JDSIRT (2013)Google Scholar
  12. 12.
    Chakir, A., Medromi, H., Sayouti, A.: Actions for data warehouse success. Journal - IJACSA 2013 4(8), August 2013Google Scholar
  13. 13.
    Sayouti, A., Medromi, H.: Book Chapter in the book, Multi-AgentSystems - Modeling, Control, Programming, Simulations and Applications. InTech, April 4, 2011. ISBN 978-953-307-174-9Google Scholar
  14. 14.
    Kimball, R.: Concevoir et déployer un data warehouse. Edition Eyrolles (2000)Google Scholar
  15. 15.
    Chakir, A., Medromi, H., Sayouti, A.: An approach multi-agent with the best practice of ITIL, to maintain the operability of a data warehouse. IJAIS 6(7), February 2014Google Scholar
  16. 16.
    Elsawah, S., Guillaume, J.H.A., Filatova, T., Rook, J., Jakeman, A.J.: A methodology for eliciting, representing, and analysing stakeholder knowledge for decision making on complex socio-ecological systems: From cognitive maps to agent-based modelsGoogle Scholar
  17. 17.
    AChakir, A., Medromi, H., Sayouti, A.: Actions for data warehouse success. Journal - IJACSA 2013 4(8), August 2013Google Scholar
  18. 18.
    Martel, J.-M.: L’aide multicritère à la décision: méthodes et applications. In: CORS - SCRO 1999 Annual Conference, Windsor, Ontario, June 7–9, 1999Google Scholar
  19. 19.
    Evans, G.: An overview of techniques for solving multiobjective mathematical programs. Management Sciences 30(11), 1268–1282 (1984)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Roy, B.: Méthodologie multicritère d’aide à la décision. Ed. Economica (1985)Google Scholar
  21. 21.
    Henriet, L.: Systèmes d’évaluation et de classification multicritères pour l’aide à la décision: Construction de modèles et procédures d’affectation. Computer Science, Université Paris Dauphine, Paris IX, French (2000)Google Scholar
  22. 22.
    Roy, B.: ELECTRE III : Un algorithme de classements fondé sur une représentation floue des préférences en présence de critères multiples. Cahiers du CERO 20(1), 3–24 (1978)zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Authors and Affiliations

  • A. Chakir
    • 1
    Email author
  • M. Chergui
    • 1
  • S. Elhasnaou
    • 1
  • H. Medromi
    • 1
  • A. Sayouti
    • 1
  1. 1.EAS Team, LISER LaboratoryENSEMCasablancaMorocco

Personalised recommendations