Advertisement

Property Based Coordination

  • Mahdi Zargayouna
  • Julien Saunier Trassy
  • Flavien Balbo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4183)

Abstract

For a multiagent system (MAS), coordination is the assumption that agents are able to adapt their behavior according to those of the other agents. The principle of Property Based Coordination (PBC) is to represent each entity composing the MAS by its observable properties, and to organize their perception by the agents. The main result is to enable the agents to have contextual behaviors. In this paper, we instantiate the PBC principle by a model, called EASI -Environment as Active Support of Interaction-, which is inspired from the Symbolic Data Analysis theory. It enables to build up an interaction as a connection point between the needs of the initiator, those of the receptor(s) and a given context. We demonstrate that thanks to PBC, EASI is expressive enough to instantiate other solutions to the connection problem. Our proposition has been used in the traveler information domain to develop an Agent Information Server dynamically parameterized by its users.

Keywords

Multiagent System Observable Property Simple Object Access Protocol Description Domain Seller Agent 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bock, H.-H., Diday, E.: Analysis of Symbolic Data, 2nd edn. Exploratory Methods for Extracting Statistical Information from Complex Data, p. 425. Springer, Heidelberg (2000)Google Scholar
  2. 2.
    Carriero, N., Gelernter, D.: How to Write Parallel Programs: A First Course, 1st edn., p. 250. MIT Press, Massachusetts (1990)Google Scholar
  3. 3.
    Carriero, N., Gelernter, D., Leichter, J.: Distributed data structures in linda. In: Proceedings of the 13th ACM symposium on Principles of programming languages, Florida, USA, pp. 236–242 (1986)Google Scholar
  4. 4.
    Davis, R., Smith, R.G.: Negotiation as a metaphor for distributed problem solving. Artificial Intelligence 20, 63–109 (1983)CrossRefGoogle Scholar
  5. 5.
    Ferber, J., Gutknecht, O., Jonker, C., Muller, J., Treur, J.: Organization models and behavioural requirements specification for multi-agent systems. In: Proceedings of the Fourth International Conference on Multi-Agent Systems (ICMAS 2000), Boston, USA, pp. 387–388. IEEE, Los Alamitos (2000)CrossRefGoogle Scholar
  6. 6.
    Ferber, J., Müller, J.P.: Influences and reaction: a model of situated multiagent systems. In: Proceedings of the Second International Conference on Multi-Agent Systems (ICMAS 1996), Kyoto, Japan, pp. 72–79. AAAI Press, Menlo Park (1996)Google Scholar
  7. 7.
    Platon, E., Sabouret, N., Honiden, S.: Overhearing and direct interactions: Point of view of an active environment, a preliminary study. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 121–138. Springer, Heidelberg (2005)Google Scholar
  8. 8.
    Ricci, A., Viroli, M., Omicini, A.: Programming MAS with artifacts. In: Bordini, R.H., Dastani, M., Dix, J., El Fallah Seghrouchni, A. (eds.) PROMAS 2005. LNCS, vol. 3862, pp. 206–221. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Saunier, J., Balbo, F., Badeig, F.: Environment as Active Support of Interaction. In: Weyns, D., Van Dyke Parunak, H., Michel, F. (eds.) E4MAS 2006. LNCS, vol. 4389, pp. 87–105. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  10. 10.
    Sycara, K., Decker, K., Williamson, M.: Middle-agents for the internet. In: Proceedings of the 15th Joint Conference on Artificial Intelligence (IJCAI 1997), pp. 578–583 (1997)Google Scholar
  11. 11.
    Weyns, D., Holvoet, T.: A colored petri net for regional synchronization in situated multi-agent systems. In: Proceedings of First International Workshop on Petri Nets and Coordination, Bologna, Italy, PNC (2004)Google Scholar
  12. 12.
    Zargayouna, M., Balbo, F., Trassy, J.S.: Agent information server: A middleware for traveler information. In: Dikenelli, O., Gleizes, M.-P., Ricci, A. (eds.) ESAW 2005. LNCS (LNAI), vol. 3963, pp. 14–28. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mahdi Zargayouna
    • 1
    • 2
  • Julien Saunier Trassy
    • 2
  • Flavien Balbo
    • 1
    • 2
  1. 1.Inrets – Gretia, National Institute of Transportation Research and their SecurityArcueil cedex
  2. 2.Lamsade, Paris Dauphine UniversityParis Cedex 16France

Personalised recommendations