Saturday , June 23 2018

A Methodology for Agent-Oriented Systems Development
Applied in Oil Industry

Petroleum-Gas University of Ploieşti, Romania
Blvd. Bucureşti, no. 39, Ploieşti, 100680, Romania;

Abstract: Nowadays, the oil and gas industry faces a rapid evolution which involves the use of a wide specialized software based capabilities to achieve its business targets. Software and information technology represent the framework for a variety of business processes such as exploration, well construction, production optimization and operations. Complex oil and gas facilities gather key engineering and related disciplines needed to analyze, design, engineer, and operate the facility across its entire lifecycle. A solution that is emerging today to assist the processes developed within an industrial plant (e.g. gas-oil separation plant) is represented by intelligent agents. Due to their capabilities (reactivity, social ability, mobility, veracity, rationality, and learning/adaptation) agents can successful work together to solve complex and distributed problems associated to production, storing, transport and processing the petroleum products. After a careful analysis of agent-based methodologies, the authors of the current paper have chosen ZEUS methodology for development of a multi-agents system applied in oil industry. The research work consists in: defining of agents, the inter-agent communication, associating the roles of agents, implementing, testing and evaluating the designed multi-agent system.

Keywords: Intelligent agent, multi-agent system, agent-oriented methodology, gas-oil separator.

>>Full Text
Liviu IONITA, Irina IONITA, A Methodology for Agent-Oriented Systems Development Applied in Oil Industry, Studies in Informatics and Control, ISSN 1220-1766, vol. 23 (3), pp. 239-248, 2014.

1. Introduction

In the last decades, many complex and distributed software systems, including process control system, diagnosis system, and modelling have used agent-oriented technologies (AOT). These new technology provides a new approach that aims at supporting the whole software development process (analysis, design, and implementation). The goal of AOT is to handle all phases and to offer a level of abstraction adequate to the problem to be solved, using a single, uniform concept, namely that of agents.

Agents are defined as autonomous entities, with cooperating and coordinating capacities, able to adapt to the new environment conditions and act together for accomplish a global objective. Due to these considerations, they have provided a path to build more robust intelligent applications from a different point of view.

AOT represent a natural extension to object-oriented techniques (OOT). In terms of OOT, agents can be seen as active objects. There are also main differences between objects and agents, as stated by [20]: the description of the internal state of an agent (by using notions like beliefs, goals, intentions etc.) and characterization of communication (by description of message types and the structuring of messages into protocols).

Over the past few years, researchers in various domains (computer science, information technology, engineering etc.) have worked together and have been several attempts at creating tools and methodologies for building multi-agent systems (MAS).

Although more methods and approaches have been proposed for this purpose, none of these methods have been accepted as a standard. The heterogeneous environment, the evolution of events, the probability of unexpected events occurrence, the difficulty to trace the system evolution involve producing a gap between agent oriented methods and the modelling needs of agent-based systems. A drawback of agent oriented software engineering methodologies, resulted from many discussions and research works presented in literature, is the lack of agreement on how to identify roles in the analysis phase and how to identify agent types in the design phase [22, 7].

This paper presents a methodology for building an agent-oriented system applied in oil industry. After a careful study, the authors have chosen the ZEUS methodology for multi-agent system development. MAS-GOSP is the proposed system that maps the processes of a Gas-Oil Separation Plant (GOSP) and consists in an agents` society with various specific assigned roles.

The article is organized as follows: section 2 gives the related work regarding agent-oriented methodology, section 3 contains the MAS-GOSP architecture and its functionalities, section 4 presents the experiments and the results and the final section contains the conclusion and the future work.


  1. BERNON, C., M.-P. GLEIZES, G. PICARD, P. GLIZE, The ADELFE Methodology for an Intranet System Design, In P. Giorgini, Y. Lespérance, G. Wagner, & E. Yu (Eds.), Proceedings of Agent-Oriented Information Systems, AOIS-2002,, 2002, pp. 1-15.
  1. BURMEISTER, B., Models and Methodology for Agent-oriented Analysis and Design, Working Notes of the KI 96.96-06, 1996, pp. 52.
  2. CAIRE, G., W. COULIER, F. GARIJO, J. GOMEZ, J. PAVON, F. LEAL, P. CHAINHO, P. KEARNEY, J. STARK, R. EVANS, P. MASSONET, Agent-oriented Analysis using MESSAGE/UML, In M. Wooldridge, G. Wei, & P. Ciancarini (Eds.), Agent-oriented Software Engineering II LNCS 2222. Berlin: Springer-Verlag, 2001, pp. 119-135.
  3. COLEMAN, D., P. ARNOLD, S. BODOFF, C. DOLLIN, H. GILCHRIST, Object Oriented Development. The Fusion Method, Englewood Cliffs, NJ: Prentice Hall, 1994
  4. COLLIS, J., D. NDUMU, C. VAN BUSKRIK, The ZEUS Technical Manual. Intelligent Systems Research Group, BT Labs, British Telecommunications, 1999.
  5. COSSENTINO, M., C. POTTS, A CASE Tool supported Methodology for the Design of Multi-agent Systems, In H. R. Ababnia & Y. Mun (Eds.), Proceedings of the 2002 International Conference on Software Engineering Research and Practice (SERP’02), Las Vegas, June 24-27, 2002, pp. 315-321.
  6. DASTANI, M., J. HULSTIJN, F. DIGNUM, J. JULES, C. MEYER, Issues in Multi-agent System Development, ACM Press, International Conference on Autonomous Agents Proceedings of the Third International Joint Conference on Autonomous Agents and Multi-agent Systems – Vol. 2, 2004, pp. 922-929.
  7. DELOACH, S. A., Multi-agent Systems Engineering: A Methodology and Language for Designing Agent Systems, in Proceedings of the First International Bi-conference Workshop on Agent-Oriented Information   Systems (AOIS ’99), May 1, Seattle., 1999.
  8. EVANS, R., P. KEARNEY, G. CAIRE, F. GARIJO, J. GOMEZ SANZ, J. PAVON, P. MASSONET, MESSAGE: Methodology for Engineering Systems of Software Agents, EURESCOM Conference, EDIN, 0223-0907, 2001.
  9. GARIJO, F. J., J. J. GOMEZ-SANZ, P. MASSONET, The MESSAGE Methodology for Agent-oriented Analysis and Design, Agent-Oriented Methodologies, vol. 8, 2005,               pp. 203-235.
  10. GIORGINI, P., B. HENDERSON-SELLER, Agent-Oriented Methodology: An Introduction, Idea Group     Publishing, 2005
  11. KENDALL, E. A., M. T. MALKOUN, C. JIANG, A Methodology for Developing Agent based Systems for Enterprise Integration, in P. Bernus & L. Nemes (Eds.), Modelling and Methodologies for Enterprise Integration. London: Chapman and Hall, 1996.
  12. KINNY, D., M. GEORGEFF, M., A. RAO, A Methodology and Modelling Technique for Systems of BDI Agents, Technical Note 58, Australian Artificial Intelligence Institute, also published in Proceedings of Agents Breaking Away, the 7th European Workshop on Modelling Autonomous Agents in a Multi-Agent World (MAAMAW’96), Springer-Verlag, 1996, pp. 56-71.
  13. KRUCHTEN, P., The Rational Unified Process. An Introduction. Reading, MA: Addison-Wesley, 1999.
  14. NDUMU, D., J. C. COLLIS, H. S. NWANA, L. C. LEE, The Zeus Agent Building Toolkit, BT Technology Journal, vol. 16, issue 3, 1998.
  15. NWANA, H., D. NDUMU, L. LEE, ZEUS: An Advanced Tool-Kit for Engineering Distributed Multi-Agent Systems, In: Proceedings of PAAM. 1998, pp. 377-392
  16. PADGHAM, L., M. WINIKOFF, Prometheus: A Methodology for Developing Intelligent Agents, In F. Giunchiglia, J. Odell, G. Weiß (Eds.), Agent oriented Software Engineering III Proceedings of the Third International Workshop on Agent-Oriented Software Engineering (AAMAS’02), LNCS 2585, 2002, pp. 174-185.
  17. PAVÓN, J., J. GOMEZ-SANZ, R. FUENTES, The INGENIAS Methodology and Tools, In B. Henderson-Sellers & P. Giorgini (Eds.), Agent-oriented Methodologies (Chapter 4). Hershey, PA: Idea Group, 2005.
  18. RUMBAUGH, J., M. BLAHA, W. PREMERLANI, F. EDDY, W. LORENSEN, Object-oriented Modelling and Design, Englewood Cliffs, NJ: Prentice-Hall, 1991.
  19. SAYDA, A. F., J. H. TAYLOR, Modelling and Control of Three-Phase Gravity Separators in Oil     Production Facilities, American Control Conference, 2007. ACC ’07, IEEE, 2007, pp. 4847-4853.
  20. SHOHAM, Y., Agent Oriented Programming, Stanford University Technical Report STAN-CS-90-1335, Stanford, 1990.
  21. STURM, A., D. DORI, O. SHEHORY, Single-model Method for Specifying Multi-agent Systems, ACM Press, 2003, pp. 121-128.
  22. SUKHVIR, S., PRACHI, S. RICHA, Evaluation of Agent Oriented Software Engineering (AOSE) Methodologies – A review, International Journal of Latest Research in Science and Technology, Vol.1, Issue 2, ISSN (Online): 2278-5299, 2012, pp. 94-97.
  23. WOOD, M., S. A. DELOACH, An Overview of the Multi-agent Systems Engineering Methodology, in P. Ciancarini & M. Wooldridge (Eds.), Proceedings of the 1st International Workshop on Agent-Oriented Software Engineering (AOSE-2000), LNCS 1957, Springer-Verlag, 2000, pp. 207-222.
  24. WOOLDRIDGE, M., N. R. JENNINGS, D. KINNY, The Gaia Methodology for Agent-oriented Analysis and Design, Journal Autonomous Agents and     Multi-Agent Systems, vol. 3, 2000, pp. 285-312.
  25. ZAMBONELLI, F., N. R. JENNINGS, M. WOOLDRIDGE, Developing Multi-agent Systems: The Gaia Methodology, In: ACM Transactions on Software Engineering and Methodology, vol. 12, issue 3, 2003, pp. 417-470.