Developing and Evaluating a Generic Metamodel for MAS Work Products

  • Ghassan Beydoun
  • César Gonzalez-Perez
  • Brian Henderson-Sellers
  • G. Low
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3914)


MAS development requires an appropriate methodology. Rather than seek a single, ideal methodology, we investigate the applicability of method engineering, which focuses on project-specific methodology construction from existing method fragments and provides an appealing approach to organize, appropriately access and effectively harness the software engineering knowledge of MAS methodologies. In this context, we introduce a generic metamodel to serve as a representational infrastructure to unify the work product component of MAS methodologies. The resultant metamodel does not focus on any class of MAS, nor does it impose any restrictions on the format of the system requirements; rather, it is an abstraction of how the work product elements in any MAS are structured and behave both at design time and run-time. Furthermore, in this paper we validate this representational infrastructure by analysing two well-known existing MAS metamodels. We sketch how they can be seen as subtypes of our generic metamodel, providing early evidence to support the use of our metamodel towards the construction of situated MAS methodologies.


Multiagent System Method Engineering Environment History Ontology Concept Message Action 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bernon, C., Cossentino, M., Gleizes, M., Turci, P., Zambonelli, F.: A Study of some Multi-Agent Meta-Models. In: Odell, J.J., Giorgini, P., Müller, J.P. (eds.) AOSE 2004. LNCS, vol. 3382, pp. 62–77. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Bernon, C., Gleizes, M.-P., Peyruqueou, S., Picard, G.: ADELFE, a Methodology for Adaptive Multi-Agent Systems Engineering. In: Petta, P., Tolksdorf, R., Zambonelli, F. (eds.) ESAW 2002. LNCS (LNAI), vol. 2577, pp. 156–169. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Beydoun, G., Debenham, J., Hoffmann, A.: Using Messaging Structure to Evolve Agents Roles. In: Barley, M.W., Kasabov, N. (eds.) PRIMA 2004. LNCS (LNAI), vol. 3371, pp. 18–30. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Bresciani, P., Perini, A., Giorgini, P., Giunchiglia, F., Mylopoulos, J.: A Knowledge Level Software Engineering Methodology for Agent Oriented Programming. In: Agents 2001. ACM, Montreal (2001)Google Scholar
  5. 5.
    Brinkkemper, S.: Method Engineering: Engineering of Information Systems Development Methods and Tools. Information and Software Technology 38(4), 275–280 (1996)CrossRefGoogle Scholar
  6. 6.
    Choren, R., Lucena, C.: Modeling multi-agent systems with ANote. Software and Systems Modelling 4, 199–208 (2005), doi:10.1007/s10271-004-0065-yCrossRefGoogle Scholar
  7. 7.
    Cockburn, A.: Selecting a project’s methodology. IEEE Software 17(4), 64–71 (2000)CrossRefGoogle Scholar
  8. 8.
    Cossentino, M., Potts, C.: A CASE tool supported methodology for the design of multi-agent systems. In: International Conference on Software Engineering Research and Practice (SERP 2002), Las Vegas (NV), USA (2002)Google Scholar
  9. 9.
    Durfee, E., Lesser, V.: Negotiating task decomposition and allocation using partial global planning. In: Gasser, L., Huhns, M. (eds.) Distributed Artificial Intelligence, pp. 229–244. Morgan Kaufmann, San Francisco (1989)CrossRefGoogle Scholar
  10. 10.
    Edmonds, B., Bryson, J.: The Insufficiency of Formal Design Methods - the necessity of an experimental approach. In: AAMAS 2004. ACM, New York (2004)Google Scholar
  11. 11.
    Esteva, M.: Electronic Institutions: From Specification To Development, in AI Research Insitute, UAB - Universitat Autonòma de Barcelona: Barcelona (2003)Google Scholar
  12. 12.
    Esteva, M.: Electronic Institutions: From Specification To Development (PhD thesis), in AI Research Insitute, UAB - Universitat Autonòma de Barcelona (2003)Google Scholar
  13. 13.
    Esteva, M., Cruz, D.d.l., Sierra, C.: ISLANDER: an electronic institutions editor. In: International Conference on Autonomous Agents & Multiagent Systems (AAMAS 2002). ACM, Italy (2002)Google Scholar
  14. 14.
    Ferber, J., Drogoul, A.: Using Reactive Multi-Agent Systems in Simulation and Problem Solving. In: Avouris, L. (ed.) Distributed AI: Theory and Praxis. Kluwer, Brussels (1992)Google Scholar
  15. 15.
    FIPA: Methodology Glossary - FIPAMG (2003)Google Scholar
  16. 16.
    Giunchiglia, F., Mylopoulos, J., Perini, A.: The Tropos Software Development Methodology: Processes, Models and Diagrams. In: Giunchiglia, F., Odell, J.J., Weiss, G. (eds.) AOSE 2002. LNCS, vol. 2585, pp. 162–173. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Guessoum, Z., Rejeb, L., Durand, R.: Using Adaptive Multi-Agent Systems to Simulate Economic Models. In: AAMAS 2004. ACM, New York (2004)Google Scholar
  18. 18.
    Henderson-Sellers, B.: Method engineering for OO systems development. Comm. ACM 46(10), 73–78 (2003)CrossRefGoogle Scholar
  19. 19.
    Henderson-Sellers, B., Bohling, J., Rout, T.: Creating the OOSPICE Model Architecture - a Case of Reuse. Software Process Improvement and Practice 8(1), 41–49 (2004)CrossRefGoogle Scholar
  20. 20.
    Henderson-Sellers, B., Giorgini, P. (eds.): Agent-Oriented Methodologies. Idea Group, Hershey (2005)Google Scholar
  21. 21.
    Henderson-Sellers, B., Simons, A., Younessi, H.: The OPEN Toolbox of Techniques. The OPEN Series. Addison-Wesley Longman, Harlow, Essex (1998)Google Scholar
  22. 22.
    Hogg, T., Williams, C.: Solving the Really Hard Problems with Cooperative Search. In: 11th National Conference on Artificial Intelligence. MIT Press, Washington (1993)Google Scholar
  23. 23.
    Horlait, E.: Mobile Agents for Telecommunication Applications (Innovative Technology Series: Information Systems and Networks). Kogan Page, Portland (2004)Google Scholar
  24. 24.
    Hunsberger, L., Grosz, B.J.: A combinatorial auction for collaborative planning. In: 4thInternational Conference on Multi-Agent Systems, ICMAS 2000 (2000)Google Scholar
  25. 25.
    Luger, G.F.: AI: Structures and Strategies for Complex Problem Solving. Addison Wesley, Reading (2002)Google Scholar
  26. 26.
    Martin, J., Odell, J.: Object-Oriented Methods: A Foundation. Prentice-Hall, Englewood Cliffs (1995)Google Scholar
  27. 27.
    Odell, J., Nodine, M., Levy, R.: A Metamodel for Agents, Roles, and Groups. In: Odell, J.J., Giorgini, P., Müller, J.P. (eds.) AOSE 2004. LNCS, vol. 3382, pp. 78–92. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  28. 28.
    Padgham, L., Winikoff, M.: Developing Intelligent Agent Systems. A Practical Guide 1, 225 (2004)Google Scholar
  29. 29.
    Pfeifer, R., Sheier, C.: Understanding Intelligence. MIT Press, Cambridge (2001)Google Scholar
  30. 30.
    Ralyté, J., Rolland, C.: An Assembly Process Model for Method Engineering. In: Dittrich, K.R., Geppert, A., Norrie, M.C. (eds.) CAiSE 2001. LNCS, vol. 2068, p. 267. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  31. 31.
    Russell, S., Norvig, P.: Artificial Intelligence, A modern Approach, the intelligent agent book. Prentice Hall, Englewood Cliffs (2003)zbMATHGoogle Scholar
  32. 32.
    Silva, V., Choren, R., Lucena, C.: Using the MAS-ML to Model a Multi-Agent System. In: Lucena, C., Garcia, A., Romanovsky, A., Castro, J., Alencar, P.S.C. (eds.) SELMAS 2003. LNCS, vol. 2940, pp. 129–148. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  33. 33.
    Silva, V., Lucena, C.: From a Conceptual Framework for Agents and Objects to a Multi-Agent System Modeling Language. Autonomous Agents and Multi-Agent Systems 8, 1–45 (2004)Google Scholar
  34. 34.
    Tidhar, G., Heinze, C., Goss, S., Murray, G., Appla, D., Lloyd, I.: Using Intelligent Agents in Military Simulation or Using Agents Intelligently. In: 11th Conference on Innovative Applications of AI. MIT Press, Orlando (1999)Google Scholar
  35. 35.
    Wooldridge, M.: Reasoning About Rational Agents. MIT Press, Cambridge (2000)zbMATHGoogle Scholar
  36. 36.
    Wooldridge, M., Jennings, N.R., Kinny, D.: The Gaia Methodology for Agent-Oriented Analysis and Design. In: Autonomous Agents and Multi-Agent Systems. Kluwer Academic Publishers, The Netherlands (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ghassan Beydoun
    • 1
    • 2
  • César Gonzalez-Perez
    • 1
    • 2
  • Brian Henderson-Sellers
    • 2
  • G. Low
    • 1
  1. 1.School of Information Systems, Technology and ManagementUniversity of New South WalesSydneyAustralia
  2. 2.Faculty of Information TechnologyUniversity of Technology of SydneySydneyAustralia

Personalised recommendations