Agent/Group/Role Organizational Model to Simulate an Industrial Control System
The modeling of complex systems is generally based on the decomposition of their components into sub-systems easier to handle. This division has to be made in a methodical way. In this paper, we introduce an industrial control system modeling and simulation based on the Multi-Agent System (MAS) methodology AALAADIN and more particularly the underlying conceptual model Agent/Group/Role (AGR). Indeed, in this division using AGR model, the overall system is decomposed into sub-systems in order to improve the understanding of regulation and control systems, and to simplify the implementation of the obtained agents and their groups, which are implemented using the Multi-Agents Development KIT (MAD-KIT) platform. This approach appears to us to be the most appropriate for modeling of this type of systems because, due to the use of MAS, it is possible to model real systems in which very complex behaviors emerge from relatively simple and local interactions between many different individuals, therefore a MAS is well adapted to describe a system from the standpoint of the activity of its components, that is to say when the behavior of the individuals is complex (difficult to describe with equations). The main aim of this approach is the take advantage of the performance, the scalability and the robustness that are intuitively provided by MAS.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1132521Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1108
 P. A. Fishwick, “Simulation Model Design and Execution. Building Digital Worlds,” Prentice Hall,1995.
 M. Sonnessa, “Modelling and simulation of complex systems (doctoral dissertation),” PhD Thesis in “Cultura e impresa,” University of Torino, Italy, 2004.
 R. E. Shannon, “Simulation modeling and methodology,” Proceedings of the 76 bicentennial conference on Winter simulation, 1976, pp. 9-15.
 C. Oussalah, “Modèles hiérachisés multi-vues pour le support de raisonnement dans les domaines techniques,” Technical report, 1988.
 R.G. Ingalls, “¬Introduction to simulation,” Proceedings of the 33nd conference on Winter simulation. IEEE Computer Society, 2001, pp. 7- 16.
 R. E. Shannon, “Introduction to the art and science of simulation,” Proceedings of the 30th conference on Winter simulation. IEEE Computer Society Press, 1998, pp. 7-14.
 P. A. Fishwick, “Computer simulation: growth through extension,” Transactions of the Society for Computer Simulation International, 14(1), 1997, pp. 13–23.
 H. Vangheluwe, “Foundations of modelling and simulation of complex systems,” Electronic communication of the EASST, 10: Graph Transformation and Visual Modeling Techniques, 2008.
 A. Simon, “The sciences of the artificial,” Cambridge (MA): MIT Press, 1969.
 L. V. Bertalanffy, “Théorie générale des systèmes,” Dunod, 1968.
 O. Gutknecht, and J. Ferber, “The MadKit agent plateforme architecture,” Laboratoire d'Informatique, Robotique et Microélectronique de Montpellier, 2000.
 J. Ferber, and O. Gutknecht, “Aalaadin: A meta-model for the analysis and design of organizations in multi-agent systems,” ICMAS (International Conference on Multi-Agent Systems), Paris, Y. Demazeau (ed), IEEE Press, 1998, pp. 128-135.
 B. Chaib-Draa, “Agent et Système Multi – Agents,” Université Laval, Quebec (Canada), 1999.
 J. Ferber, “Les systèmes multi-agents: vers une intelligence collective. Informatique,” intelligenceArtificielle. Intereditions Paris, 1995.
 J. Ferber, “Les Systèmes Multi-Agents: Un Aperçu Général,” Revue Technique et Science Informatiques, Hermes-Lavoisier, 1997.
 F. Michel, J. Ferber and A. Drogoul, “Multi-Agent Systems and Simulation: A survey from the agent’s community perspective, ” Revue Technique et Science Informatiques, Multi-Agent systems: simulation and application edited by A. M. Uhrmacher, D. Weyns– CRC Press- Taylor and Francis Group , 2009, pp. 3-52.
 N. Seddari, M. Redjimi and S. Boukelkoul, “Using of DEVS and MAS Tools for Modeling and Simulation of an Industrial Steam Generator,” CIT 22, 2014, pp.171–189.doi:10.2498/cit.1002348.
 A. H. Bond and L. Gasser, “Readings in Distributed Artificial Intelligence,” Morgan Kaufmann Publishers: San Mateo, CA, 1988.
 S. Franklin and A. Graesser, “Is it an agent, or just a program?: A taxonomy for autonomous agents,” In J. P. Mueller, M. Wooldridge, and N. R. Jennings, editors, Intelligent Agents III: Theories, Architectures, and Languages (LNAI Volume 1193), 1997, pp 21-35.
 C. A. Iglesias, M. Garijo, J. C. Gonzàlez and J. R. Velasco, “Analysis ans design of multi-agent systems using mas-commonkads,” In AAAI'97 Workshop on Agent Theories, Architectures and Languages, Providence, RI, 1997.
 J. Ferber, O. Gutknecht,and F. Michel, “From agents to organizations: An organizational view of multi-agent systems,” In Paolo Giorgini, Jörg P. Müller, and James Odell, editors, AOSE, volume 2935 of Lecture Notes in Computer Science, 2003,pp. 214–230.
 N. Seddari, M. Redjimi and L. Benoudina, “Operational approach for modeling and simulation of an industrial process,” In IEEE International Conference on Computer Application Technology (ICCAT), 2013.DOI: 10.1109/ICCAT.2013.6522031.
 N. Seddari and M. Redjimi, “Multi-Agent Modeling of a Complex System,” In IEEE 3rd International Conference on Information Technology and e_Services (ICITeS), Sousse – Tunisia, 2013.DOI: 10.1109/ICITeS.2013.6624072.
 F. J. Ferber and O. Gutknecht, “Generic Simulation Tools Based on MAS Organization” LIRMM Laboratoire d’Informatique, Robotique et Micro-électronique de Montpellier, 2001.
 J. Ferber, O. Gutknecht and F. Michel, “From agents to organizations: An organizational view of multi-agent systems,” In Paolo Giorgini, JörgP. Müller, and James Odell, editors, AOSE, volume 2935 of Lecture Notes in Computer Science, 2013, pp. 214–230.