Agents and Multi-Agent Systems

  • Marie-Pierre Gleizes
  • Valérie CampsEmail author
  • Anthony Karageorgos
  • Giovanna Di Marzo Serugendo
Part of the Natural Computing Series book series (NCS)


MAS is well-known and efficient paradigm to deal with complexity and distribution. They are composed of interacting agents evolving in a common environment in order to execute a global task. Lot of works have been done on these systems and currently, because targeted applications need dynamics, openness and robustness, the systems to be done must have the ability to self-adapt. Naturally, self-organisation is introduced in these systems to enable them to get open, robust and adaptive MASs. In this chapter, we present the three main concepts of the MAS domain, agent, MAS and environment, and their properties, and indicate the links between MASs and self-organisation.


  1. 1.
    Baez-Barranco, J., Stratulat, T., Ferber, J.: A unified model for physical and social environments. In: Environments for Multi-Agent Systems III. LNCS, vol. 4389, pp. 41–50 (2007) CrossRefGoogle Scholar
  2. 2.
    Bonabeau, E., Dorigo, M., Théraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, London (1999) zbMATHGoogle Scholar
  3. 3.
    Capera, D., Georgé, J.P., Gleizes, M.P., Glize, P.: The AMAS theory for complex problem solving based on self-organizing cooperative agents. In: 1st International TAPOCS Workshop at IEEE 12th WETICE, pp. 383–388. IEEE Press, New York (2003) Google Scholar
  4. 4.
    Clarke, E.M., Wing, J.M.: Formal methods: state of the art and future directions. ACM Comput. Surv. 28(4), 626–643 (1996) CrossRefGoogle Scholar
  5. 5.
    De Wolf, T.: Analysing and engineering self-organising emergent applications. Ph.D. thesis, Department of Computer Science, K.U. Leuven, Leuven, Belgium (2007).
  6. 6.
    Di Marzo Serugendo, G.: Self-organisation in MAS. In: Di Marzo Serugendo, G., Gleizes, M.P., Karageorgos, A. (eds.) Tutorial at the 4th International Central and Eastern European Conference on Multi-Agent Systems (CEEMAS’05), Budapest, Hungary, 15 September 2005 Google Scholar
  7. 7.
    Document Title Fipa: FIPA communicative act library specification (2001).
  8. 8.
    Ferber, J.: Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence. Addison-Wesley, Reading (1999) Google Scholar
  9. 9.
    Ferber, J., Gutknecht, O.: Alaadin: a meta-model for the analysis and design of organizations in multi-agent systems. In: ICMAS, pp. 128–135. IEEE Computer Society, Los Alamitos (1998) CrossRefGoogle Scholar
  10. 10.
    Ferber, J., Jacopin, E.: The framework of eco problem solving. In: Decentralized Artificial Intelligence, vol. II (1991) Google Scholar
  11. 11.
    Hassas, S., Castelfranchi, C., Di Marzo Serugendo, G., Karageorgos, A.: Self-organising mechanisms from social and business/economics approaches. Informatica 30(1), 63–71 (2006) Google Scholar
  12. 12.
    Labrou, Y., Finin, T.: KQML as an Agent Communication Language. MIT Press, Cambridge (1994) Google Scholar
  13. 13.
    Mano, J., Bourjot, C., Lopardo, G., Glize, P.: Bio-inspired mechanisms for artificial self-organised systems. Informatica 30(1), 55–62 (2006) Google Scholar
  14. 14.
    Odell, J., Parunak, H., Bauer, B.: Representing agent interaction protocols in UML. In: OMG Document ad/99-12-01. Intellicorp Inc, pp. 121–140. Springer, Berlin (2000) Google Scholar
  15. 15.
    Odell, J., Parunak, H., Fleisher, M., Brueckner, S.: Modeling agents and their environment. In: AOSE 2002. LNAI, vol. 2585 (2003) Google Scholar
  16. 16.
    Parunak, H.V.D., Brueckner, S.: Engineering Swarming Systems, pp. 341–376. Kluwer Academic, Dordrecht (2004) Google Scholar
  17. 17.
    Rao, A.S., Georgeff, M.P.: BDI agents: from theory to practice. In: ICMAS’95, pp. 312–319 (1995) Google Scholar
  18. 18.
    Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice Hall Series. Prentice Hall, New York (1995) zbMATHGoogle Scholar
  19. 19.
    Slaby, J., Welch, L., Work, P.: Toward certification of adaptive distributed systems. In: Real-time and Embedded Systems Workshop (2006) Google Scholar
  20. 20.
    Weiß, G.: Multiagent Systems, a Modern Approach to Distributed Artificial Systems. MIT Press, Cambridge (1999) Google Scholar
  21. 21.
    Weyns, D., Parunak, H.V.D., Michel, F., Holvoet, T., Ferber, J.: Environments for multiagent systems: state-of-the-art and research challenges. In: Environments for Multiagent Systems. LNAI, vol. 3477 (2005) CrossRefGoogle Scholar
  22. 22.
    Wooldridge, M.: An Introduction to Multi-Agent Systems. Wiley, New York (2002) Google Scholar
  23. 23.
    Wooldridge, M., Ciancarini, P.: Agent-Oriented Software Engineering: the State of the Art. LNAI, vol. 1957 (2002) CrossRefGoogle Scholar
  24. 24.
    Wooldridge, M., Jennings, N.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10(2), 115–152 (1995) CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Marie-Pierre Gleizes
    • 1
  • Valérie Camps
    • 1
    Email author
  • Anthony Karageorgos
    • 2
  • Giovanna Di Marzo Serugendo
    • 3
  1. 1.IRITUniversité Paul SabatierToulouseFrance
  2. 2.Technological Educational Institute of LarissaLarissaGreece
  3. 3.Birkbeck CollegeUniversity of LondonLondonUK

Personalised recommendations