Journal of Simulation

, Volume 7, Issue 3, pp 137–143 | Cite as

Simulation-based development and validation of multi-agent systems: AOSE and ABMS approaches

Article

Abstract

This paper briefly surveys an emerging research area: the integration of agent-oriented software engineering (AOSE) and agent-based modelling and simulation (ABMS). Both AOSE and ABMS are well-established research areas in the agent-based computing domain. Specifically, this paper provides an overview of the main simulation-based methodologies for developing multi-agent systems (MASs) that describe interesting ABMS application domains where the integration of AOSE and ABMS can benefit MAS development.

Keywords

agent-based modelling agent-oriented software engineering multi-agent systems 

References

  1. Bernon C, Gleizes M-P, Peyruqueou S and Picard G (2003). ADELFE: A methodology for adaptive multi-agent systems engineering. Engineering Societies in the Agents World III, Lecture Notes in Computer Science, Vol. 2577, pp 156–169.CrossRefGoogle Scholar
  2. Bernon C, Cossentino M and Pavón J (2005). Agent oriented software engineering. Knowledge Engineering Review 20 (2): 99–116.CrossRefGoogle Scholar
  3. Bernon C, Gleizes MP and Picard G (2007). Enhancing self-organising emergent systems design with simulation. In: O’Hare G, O’Grady M, Ricci A and Dikenelli O (eds). Proceedings of the International Workshop on Engineering Societies in the Agents World (ESAW) held in Dublin, Ireland, in 2006, September, Springer-Verlag, LNCS, Vol. 4457, pp 284–299.Google Scholar
  4. Bresciani P, Giorgini P, Giunchiglia F, Mylopoulos J and Perini A (2004). Tropos: An agent-oriented software development methodology. Journal of Autonomous Agents and Multi-Agent Systems 8 (3): 203–236.CrossRefGoogle Scholar
  5. Collier NT and North MJ (2011). Repast HPC: A platform for large-scale agent-based modeling. In: Dubitzky W, Kurowski K and Schott B (eds). Large-Scale Computing Techniques for Complex System Simulations. Wiley-IEEE Computer Society Press: Hoboken, NJ.Google Scholar
  6. Conzelmann G et al (2004). Analyzing the potential for market power using an agent-based modelling and simulation approach: Results of a detailed U.S. power market simulation. In: Proceedings of the International Conference on Computing, Communication and Control Technologies, Vol. VI, The University of Texas at Austin and International Institute of Informatics and Systemics: Austin, TX, pp 109–114.Google Scholar
  7. Cossentino M (2005). From requirements to code with the PASSI methodology. In: Henderson-Sellers B and Giorgini P (eds). Agent-Oriented Methodologies. Idea Group: Hershey, PA.Google Scholar
  8. Cossentino M, Fortino G, Garro A, Mascillaro S and Russo W (2008). PASSIM: A simulation-based process for the development of multi-agent systems. International Journal of Agent-Oriented Software Engineering 2 (2): 132–170.CrossRefGoogle Scholar
  9. Darley V and Outkin AV (2007). A NASDAQ Market Simulation: Insights on a Major Market from the Science of Complex Adaptive Systems. World Scientific Publishing: Singapore.CrossRefGoogle Scholar
  10. Fortino G and Russo W (2012). ELDAMeth: A methodology for simulation-based prototyping of distributed agent systems. Information and Software Technology 54 (6): 608–624.CrossRefGoogle Scholar
  11. Fortino G, Garro A and Russo W (2005). An integrated approach for the development and validation of multi agent systems. Computer Systems Science and Engineering 20 (4): 94–107.Google Scholar
  12. Gardelli L, Viroli M, Casadei M and Omicini A (2008). Designing self-organising environments with agents and artifacts: A simulation-driven approach. International Journal of Agent-Oriented Software Engineering 2 (2): 171–195.CrossRefGoogle Scholar
  13. Garro A and Russo W (2010). easyABMS: A domain-expert oriented methodology for agent based modeling and simulation. Simulation Modeling Practice and Theory 18 (10): 1453–1467.CrossRefGoogle Scholar
  14. Gomez-Sanz JJ, Fernandez CR and Arroyo J (2010). Model driven development and simulations with the INGENIAS agent framework. In: Simulation Modelling Practice and Theory, Vol. 18, Issue 10, Simulation-Based Design and Evaluation of Multi-Agent Systems, November, pp 1468–1482.Google Scholar
  15. Himmelspach J, Röhl M and Uhrmacher AM (2008). Component based models and simulation experiments for multi-agent systems in James II. In: Proceedings of the 6th International Workshop, From Agent Theory to Agent Implementation (AT2AI), held jointly with AAMAS, Estoril, Portugal, 13 May.Google Scholar
  16. Inchiosa ME and Parker MT (2002). Overcoming design and development challenges in agent-based modeling using ASCAPE. In: Proceedings of the National Academy of Sciences, Vol. 99, Issue 90003, pp 7304–7308.Google Scholar
  17. Lauren MK and Stephen RT (2002). Map-aware non-uniform Automata (MANA): A New Zealand approach to scenario modelling. Journal of Battlefield Technology 5 (1): 27.Google Scholar
  18. Logan B and Theodoropoulos G (2001). The distributed simulation of multi-agent systems. In: Uhrmacher AM, Fishwick PA and Zeigler BP (eds). Proceedings of the IEEE 89, IEEE, pp 174–186.Google Scholar
  19. Luke S, Cioffi-Revilla C, Panait L, Sullivan K and Balan G (2005). MASON: A multi-agent simulation environment. Simulation: Transactions of the Society for Modeling and Simulation International 82 (7): 517–527.CrossRefGoogle Scholar
  20. Macal CM and North MJ (2007). Agent-based modeling and simulation: Desktop ABMS. In: Proceedings of the 39th Conference on Winter Simulation: 40 Years! The Best Is Yet To Come, held in Washington DC, 9–12 December, IEEE Press: Piscataway, NJ, pp 95–106.Google Scholar
  21. Macal CM and North MJ (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation 4 (3): 151–162.CrossRefGoogle Scholar
  22. Martelli M, Mascardi V and Zini F (1999). Specification and simulation of multi-agent systems in CaseLP. In: Meo MC and Ferro MV (eds). Proceedings of Appia-Gulp-Prode Joint Conference on Declarative Programming, L’Aquila, Italy, pp 13–28.Google Scholar
  23. McIntosh GC, Galligan DP, Anderson MA and Lauren MK (2012). Recent developments in the MANA agent-based model. In: Edited and published by the Naval Postgraduate School, The Scythe: Proceedings and Bulletin of the International Data Farming Community, Monterey, CA USA, Issue 1, pp 38–39.Google Scholar
  24. Michel F, Ferber J and Drogoul A (2009). Title: Multi-agent Systems and Simulation: A Survey from the Agent Community's Perspective Chapter 1, CRC Press: Boca Raton, FL, pp 3–52.Google Scholar
  25. Minar N, Burkhart R, Langton C and Askenazi M (1996). Title: The Swarm simulation system: A toolkit for building multi-agent simulations, Working Paper 96-06-042. Santa Fe Institute: Santa Fe, NM.Google Scholar
  26. Molesini A, Denti E and Omicini A (2007). From AOSE methodologies to MAS infrastructures: The SODA case study. In: Proceedings of the 8th International Workshop, Engineering Societies in the Agents World (ESAW’07), Athens, Greece, 22–24 October.Google Scholar
  27. Niazi M, Hussain A and Kolberg M (2009). Verification and validation of agent-based simulations using the VOMAS approach. In: Proceedings of the Third Workshop on Multi-Agent Systems and Simulation’09, as part of MALLOW 09, Torino, Italy, 7–11 September.Google Scholar
  28. North MJ, Collier NT and Vos JR (2006). Experiences creating three implementations of the Repast agent modeling toolkit. ACM Transactions on Modeling and Computer Simulation 16 (1): 1–25.CrossRefGoogle Scholar
  29. North MJ et al (2010). Multi-scale agent-based consumer market modeling. Complexity 15 (5): 37–47.Google Scholar
  30. North MJ et al (2013). Complex adaptive systems modeling with Repast simphony. In: Complex Adaptive Systems Modeling, Springer: Heidelberg, Federal Republic of Germany.Google Scholar
  31. Outkin AV (2012). An agent-based model of the NASDAQ stock market: Historic validation and future directions. Presented at the 2012 CSSSA Annual Conference, Santa Fe, New Mexico, 18–21 September.Google Scholar
  32. Padgham L and Winikoff M (2005). Prometheus: A practical agent-oriented methodology. In: Henderson-Sellers B and Giorgini P (eds). Agent-Oriented Methodologies. Idea Group: Hershey, PA.Google Scholar
  33. Parker J and Epstein J (2011). A distributed platform for global-scale agent-based models of disease transmission. ACM Transactions on Modeling and Computer Simulation 22 (1): 2–25.CrossRefGoogle Scholar
  34. Pavon J, Sansores C and Gomez-Sanz JJ (2008). Modelling and simulation of social systems with INGENIAS. International Journal of Agent-Oriented Software Engineering 2 (2): 196–221.CrossRefGoogle Scholar
  35. Railsback SF, Harvey BC, Jackson SK and Lamberson RH (2009). InSTREAM: The individual-based stream trout research and environmental assessment model General Technical Report PSW-GTR-218. U.S. Department of Agriculture Forest Service, Pacific Southwest Research Station, Albany, CA.Google Scholar
  36. Sarjoughian HS, Zeigler BP and Hall SB (2001). A layered modelling and simulation architecture for agent-based system development. IEEE 89 (2): 201–213.CrossRefGoogle Scholar
  37. Sierra C, Rodríguez-Aguilar JA, Noriega P, Esteva M and Arcos JL (2004). Engineering multi-agent systems as electronic institutions. Novática 170.Google Scholar
  38. Wilensky U (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.Google Scholar
  39. Wooldridge M (2009). An Introduction to MultiAgent Systems, 2nd edn. John Wiley & Sons: New York.Google Scholar
  40. Wooldridge M, Jennings NR and Kinny D (2000). The Gaia methodology for agent-oriented analysis and design. Journal of Autonomous Agents and Multi-Agent Systems 3 (3): 285–312.CrossRefGoogle Scholar

Copyright information

© Operational Research Society 2013

Authors and Affiliations

  1. 1.DEIS, DIMES, University of CalabriaRendeItaly
  2. 2.Argonne National LaboratoryArgonneUSA

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