BECAMEDA: A Customizable Method to Specify and Verify the Behavior of Multi-agent Systems

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)

Abstract

Multi-Agent paradigm offers a viable solution to the increasing needs for smart and crisis system that reacts accordingly to the environment changes. The researches have largely focused on studying the development of the various approaches that deals with designing and implementing the multi-agent system. However, there is a lack in approaches that treat in depth the specification aspect of the Multi-Agent systems engineering process, which is important to better define and describe the behavior of the agents. This paper is interested in studying the specification and the verification of Multi-Agent behavior, it proposes in consequence an effective method called BECAMEDA. It is based on an iterative process that is useful to understand the system starting from goals identification that the system expects to achieve through the formal verification of the system properties. The method is illustrated by an example of a Crisis Management system.

Keywords

Multi-agent Specification Verification Behavioral model Model checking 

References

  1. 1.
    Mattei, S., Bisgambiglia, P.A., Delhom, M., Vittori, E.: Towards discrete event multi agent platform specification. In: Third International Conference on Computational Logics, Algebras, Programming, Tools, and Benchmarking, pp. 14–21 (2012)Google Scholar
  2. 2.
    Chuanjun, R., Hongbing, H., Shiyao, J.: Specification of agent in complex adaptive system. In: Computer Science and Computational Technology, ISCSCT 2008, vol. 2, pp. 210–216 (2008)Google Scholar
  3. 3.
    Sharma, M., Firdaus, M., Chatterjee, R.K., Sarkar, A.: Constraint specification in multi-agent system. In: Region 10 Conference (TENCON), pp. 2404–2409. IEEE (2016)Google Scholar
  4. 4.
    Subburajand, V.H., Urban, J.E.: Issues and challenges in building a framework for reactive agent systems. In: Complex, Intelligent and Software Intensive Systems (CISIS), pp. 600–605. IEEE (2010)Google Scholar
  5. 5.
    Bounabat, B., Romadi, R., Labhalla, S.: Designing multiagent reactive systems: a specification method based on reactive decisional agents. In: Pacific Rim International Workshop on Multi-Agents. LNAI, vol. 1733, pp. 197–210. Springer, Heidelberg (1999)Google Scholar
  6. 6.
    Aaroud, A., Labhalla, S.E., Bounabat, B.: Modelling the handover function of global system for mobile communication. Int. J. Model. Simul. 25(2), 99–105 (2005)CrossRefGoogle Scholar
  7. 7.
    Romadi, R., Berbia, H., Bounabat, B.: Wireless sensor network simulation of the energy consumption by a multi-agents system. J. Theor. Appl. Inf. Technol. 25(1), 50–56 (2011)Google Scholar
  8. 8.
    Berrada, M.: Qualitative verification of multi-agents reactive decisional system using business process modeling notation. In: Intelligent Agent Technology, pp. 747–751. IEEE (2006)Google Scholar
  9. 9.
    Kienzle, J., Guelfi, N., Mustafiz, S.: Crisis management systems: a case study for aspect-oriented modeling. In: Transactions on Aspect-Oriented Software Development VII, pp. 1–22. Springer, Heidelberg (2010)Google Scholar
  10. 10.
    Graja, Z., Migeon, F., Maurel, C., Gleizes, M.P., Kacem, A.H.: A stepwise refinement based development of self-organizing multi-agent systems: application to the foraging ants. In: International Workshop on Engineering Multi-Agent Systems, pp. 40–57. Springer, Heidelberg (2014)Google Scholar
  11. 11.
    Pereverzeva, I., Troubitsyna, E., Laibinis, L.: Formal development of critical multi-agent systems: a refinement approach. In: Ninth European Dependable Computing Conference, pp. 156–161 (2012)Google Scholar
  12. 12.
    Chatterjee, R.K., Neha, N., Sarkar, A.: Behavioral modeling of multi agent system: high level petri net based approach. Int. J. Agent Technol. Syst. 7(1), 55–78 (2015)CrossRefGoogle Scholar
  13. 13.
    Hadj-Kacem, A., Regayeg, A., Jmaiel, M.: ForMAAD: a formal method for agent-based application design. Int. J. Web Intell. Agent Syst. 5(4), 435–454 (2007)MATHGoogle Scholar
  14. 14.
    Laouadi, M.A., Mokhati, F., Seridi-Bouchelaghem, H.: A novel organizational model for real time mas: towards a formal specification. In: Intelligent Systems for Science and Information, pp. 171–180. Springer International Publishing, Cham (2014)Google Scholar
  15. 15.
    Haqiq, A., Bounabat, B.: An extended approach for the behavioral and temporal constraints specification of reactive agent. In: 15th International Conference on Intelligent Systems Design and Applications, pp. 329–334. IEEE (2015)Google Scholar
  16. 16.
    Haqiq, A., Bounabat, B.: UML profile for modeling multi decisional reactive agent system. J. Lect. Notes Softw. Eng. 1(3), 224 (2013). ISSN:2301-3559CrossRefGoogle Scholar
  17. 17.
    Clarke, E.M.: The birth of model checking. In: 25 Years of Model Checking, pp. 1–26. Springer, Heidelberg (2008)Google Scholar
  18. 18.
    Haqiq, A., Bounabat, B.: Model checking of multi decisional reactive agent system. In: 9th International Conference on Intelligent Systems: Theories and Application, Rabat, Morocco, vol. 1, pp. 133–140 (2014)Google Scholar
  19. 19.
    Haqiq, A., Bounabat, B.: Verification of multi decisional reactive agent using SMV model checker. In: 8th IEEE International Design and Test Symposium, Marrakesh, Morocco, pp. 1–6 (2013)Google Scholar
  20. 20.
    Cimatti, A., Clarke, E., Giunchiglia, E., Giunchiglia, F., Pistore, M., Roveri, M., Sebastiani, R., Tacchella, A.: NuSMV 2: an open source tool for symbolic model checking. In: 14th Conference on Computer Aided Verification, LNCS, vol. 2404. Springer, Heidelberg (2002)Google Scholar
  21. 21.
    Bolotov, A.: A clausal resolution method for CTL branching-time temporal logic. J. Exp. Theor. Artif. Intell. 11(1), 77–93 (1999)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.ENSIASMohammed V UniversityRabatMorocco

Personalised recommendations