Autonomous Agents and Multi-Agent Systems

, Volume 28, Issue 3, pp 430–473 | Cite as

Medee Method Framework: a situational approach for organization-centered MAS

  • Sara J. Casare
  • Anarosa A. F. Brandão
  • Zahia Guessoum
  • Jaime S. SichmanEmail author


This paper presents a situational approach, called Medee Method Framework, which allows the development of organization-centered MAS in a disciplined way, even though some agent organizational (AO) models are not currently incorporated into agent-oriented software engineering (AOSE) methods. In order to do that, such a method framework proposes the composition of MAS situational methods out of method fragments according to a given project situation, by applying the principles proposed by situational method engineering. The proposed approach provides a high degree of reuse and flexibility, allowing the composition of new methods as well as the reengineering of AOSE methods based on the standards proposed by SPEM. Furthermore, it allows the user to leverage advantages of both AOSE methods and AO models in order to develop organization-centered MAS. The Medee Method Framework offers a method repository that covers different development phases, such as requirements, analysis, design, implementation, as well as the main components of a MAS application, like agents, environments, interactions, and organizations. This repository has been sourced from several AOSE methods and AO models, as Gaia, Tropos, Ingenias, PASSI, MOISE, and OperA.


Organization-centered MAS AOSE method Method fragment  Situational method 



This research has been mostly supported by FAPESPRegular research project 2009/10121-4 and international cooperation FAPESP-CNRS project 2009/54773-5., Brazil. Jaime Sichman is partially supported by CNPq, Brazil. Sara Casare was partially supported by CAPES, Brazil. Zahia Guessoum is partially supported by CNRS, France. We would like to thank the invaluable work from the reviewers that helped us to improve the paper quality and readability.


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Copyright information

© The Author(s) 2013

Authors and Affiliations

  • Sara J. Casare
    • 1
  • Anarosa A. F. Brandão
    • 1
  • Zahia Guessoum
    • 2
  • Jaime S. Sichman
    • 1
    Email author
  1. 1.Laboratório de Técnicas Inteligentes (LTI), Escola Politécnica (EP)Universidade de São Paulo (USP)São PauloBrazil
  2. 2.Equipe SMA, Laboratoire d’Informatique de Paris 6 (LIP6)Université Pierre et Marie Curie (UPMC)ParisFrance

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