Skip to main content
SpringerLink
Log in

“Engineering” Agent-Based Simulation Models?

  • Conference paper
Agent-Oriented Software Engineering XIII (AOSE 2012)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7852))

Included in the following conference series:

Abstract

Multiagent simulation emerges to be one of the “killer applications” of multiagent system technology. For several reasons, there is a serious lack of engineering approaches in developing simulation models, so connecting AOSE with Multiagent Simulation seems to end in a win-win situation. A basic prerequisite is hereby to understand the current state and challenges of developing multiagent simulations. This is the objective of this contribution.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abdou, M., Hamil, L., Gilbert, N.: Designing and building an agent-based model. In: Heppenstall, A.J., Crooks, A., See, L.M., Batty, M. (eds.) Agent-based Models in Geographical Systems, pp. 141–166. Springer (2012)

    Google Scholar 

  2. Axtell, R., Axelrod, R., Epstein, J.M., Cohen, M.D.: Aligning simulation models: A case study and results. Computational and Mathematical Organization Theory 1, 123–141 (1996)

    Article  Google Scholar 

  3. Bernon, C., Capera, D., Mano, J.-P., Videau, S., Regis, C.: Towards Self-Modelling of Metabolic Pathways. Journal of Biological Physics and Chemistry 9(1), 43–50 (2009)

    Google Scholar 

  4. Bersini, H.: UML for ABM. Journal of Artificial Societies and Social Science 15(9) (2012)

    Google Scholar 

  5. Bommel, P., Müller, J.-P.: An introduction to UML for modelling in the human and social sciences. In: Phan, D., Amblard, F. (eds.) Agent-Based Modeling and Simulation in the Human an Social Sciences, pp. 273–294. Bardwell Press, Oxford (2007)

    Google Scholar 

  6. Drogoul, A., Vanbergue, D., Meurisse, T.: Multi-agent based simulation: Where are the agents? In: Sichman, J.S., Bousquet, F., Davidsson, P. (eds.) MABS 2002. LNCS (LNAI), vol. 2581, pp. 1–15. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  7. Edmonds, B., Moss, S.: From KISS to KIDS - an ’anti-simplistic’ modelling approach. In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS (LNAI), vol. 3415, pp. 130–144. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  8. Epstein, J.M.: Generative Social Science: Studies in Agent-Based Computational Modeling. Princeton University Press (2007)

    Google Scholar 

  9. Fehler, M., Klügl, F., Puppe, F.: Techniques for analysis and calibration of multi-agent simulations. In: Gleizes, M.-P., Omicini, A., Zambonelli, F. (eds.) ESAW 2004. LNCS (LNAI), vol. 3451, pp. 305–321. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  10. Frantz, F.K.: A taxonomy of model abstraction techniques. In: Proceedings of the 27th Conference on Winter Simulation, WSC 1995, pp. 1413–1420. IEEE Computer Society (1995)

    Google Scholar 

  11. Fuentes-Fernandez, R., Galan, J.M., Hassan, S., Lopez-Paredes, A., Pavon, J.: Application of model driven techniques for agent-based simulation. In: Advances in Practical Applications of Agents and Multiagent Systems, PAAMS 2010, Salamanca, Spain (April 2010)

    Google Scholar 

  12. Galan, J.M., Izquierdo, L.R., Izquierdo, S.S., Santos, J.I., del Olmo, R., Lopez-Paredes, A., Edmonds, B.: Infrastructures and tools for multaigent systems for the new generation of distributed systems. Engineering Applications of Artificial Intelligence 27(7), 1095–1097 (2011)

    Google Scholar 

  13. Garro, A., Russo, W.: easyABM: A domain-expert oriented methodology for agent-based modeling and simulation. Simulation Modelling Practice and Theory 18, 1453–1467 (2010)

    Article  Google Scholar 

  14. Ghorbani, A., Bots, P., Dignum, V., Dijkema, G.: MAIA: a framework for developing agent-based social simulations. Journal of Artificial Societies and Social Simulation 16(2), 9 (2013)

    Google Scholar 

  15. Gilbert, N.: Agent-based Models. In: Quantitative Applications in Social Science. Sage Publications (2007)

    Google Scholar 

  16. Gilbert, N., Troitzsch, K.G.: Simulation for the social scientist, 2nd edn. Open University Press (2005)

    Google Scholar 

  17. Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., Goss-Custard, J., Grand, T., Heinz, S.K., Huse, G., Huth, A., Jepsen, J.U., Jøorgensen, C., Mooij, W.M., Müller, B., Peer, G., Piou, C., Railsback, S.F., Robbins, A.M., Robbins, M.M., Rossmanith, E., Rüger, N., Strand, E., Souissi, S., Stillman, R.A., Vabøo, R., Visser, U., DeAngelis, D.L.: A standard protocol for describing individual-based and agent-based models. Ecological Modelling 198, 115–126 (2006)

    Article  Google Scholar 

  18. Grimm, V., Railsback, S.F.: Individual-Based Modeling and Ecology. Princeton University Press (2005)

    Google Scholar 

  19. Grimm, V., Railsback, S.F.: Designing, formulating, and communicating agent-based models. In: Heppenstall, A.J., Crooks, A., See, L.M., Batty, M. (eds.) Agent-based Models in Geographical Systems, pp. 361–378. Springer (2012)

    Google Scholar 

  20. Gürcan, O., Bernon, C., Türker, K.S.: Towards a self-organized agent-based simulation model for exploration of human synamptic connections. In: CoRR 2012 (2012)

    Google Scholar 

  21. Haefner, J.W.: Modeling Biological Systems – Principles and Applications, 2nd edn. Springer, New York (2005)

    MATH  Google Scholar 

  22. Heath, B., Hill, R., Ciarallo, F.: A survey of agent-based modeling practices (january 1998 to july 2008). Journal of Artificial Societies and Social Simulation 12(4), 9 (2009)

    Google Scholar 

  23. Helbing, D., Balietti, S.: Agent-based modeling. In: Helbing, D. (ed.) Social Self-Organization: Understanding Complex Systems, pp. 25–70. Springer (2012)

    Google Scholar 

  24. Izquierdo, L.R., Polhill, J.G.: Is your model susceptible to floating-point errors? Journal of Artificial Societies and Social Simulation 9(4), 4 (2006)

    Google Scholar 

  25. Junges, R., Klügl, F.: How to design agent-based simulation models using agent learning. In: Rose, O., Uhrmacher, A.M. (eds.) Winter Simulation Conference, WSC 2012, Berlin, Germany, December 9-12, p. 239 (2012)

    Google Scholar 

  26. Klügl, F.: A validation methodology for agent-based simulations. In: Proc. of the ACM SAC Symposium “Advances in Computer Simulation, Ceara, Brasil (2008)

    Google Scholar 

  27. Klügl, F.: Multiagent simulation model design strategies. In: Proceedings of the Second Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW), Turin, Italy, September 7-10. CEUR Workshop Proceedings, vol. 494 (2009)

    Google Scholar 

  28. Klügl, F., Davidsson, P.: First steps towards a meta-model for mabs. In: 10th European Workshop on Multiagent Systems, Dublin (December 2012)

    Google Scholar 

  29. Klügl, F., Oechslein, C., Puppe, F., Dornhaus, A.: Multi-agent modelling in comparison to standard modelling. Simulation News Europe 40, 3–9 (2004)

    Google Scholar 

  30. Kubera, Y., Mathieu, P., Picault, S.: IODA: An interaction-oriented approach for multi-agent based simulations. Autonomous Agents and Multi-Agent Systems 23(3), 303–343 (2011)

    Article  Google Scholar 

  31. Law, A.M.: Simulation Modeling & Analysis, International Edition, 4th edn. McGraw-Hill (2007)

    Google Scholar 

  32. Louloudi, A., Klügl, F.: Immersive face validation: A new validation technique for agent-based simulation. In: Proc. of the 6th Workshop on Multiagent Systems and Simulation (MAS&S), at FEDCIS 2012 (2012)

    Google Scholar 

  33. Miller, J.H., Page, S.E.: Complex Adaptive Systems – an introduction to computational models of social life. Princeton University Press (2007)

    Google Scholar 

  34. Norling, E., Edmonds, B., Meyer, R.: Informal approaches to developing simulation models. In: Edmonds, B., Meyer, R. (eds.) Simulating Social Complexity, Understanding Complex Systems, pp. 39–55. Springer (2013)

    Google Scholar 

  35. North, M.J., Macal, C.M.: Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation. Oxford University Press (2007)

    Google Scholar 

  36. Oechslein, C.: Vorgehensmodell mit integrierter Spezifikations- und Implementierungssprache für Multiagentensimulationen (Process Model with Integrated Specification and Implemenatation Language for Multiagent Simulations). PhD thesis, Institute of Computer Science, Universität Würzburg (2004)

    Google Scholar 

  37. Oechslein, C., Klügl, F., Herrler, R., Puppe, F.: Uml for behavior-oriented multi-agent simulations. In: Dunin-Keplicz, B., Nawarecki, E. (eds.) CEEMAS 2001. LNCS (LNAI), vol. 2296, pp. 217–226. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  38. Palit, I., Phelps, S., Ng, W.L.: Can a zero-intelligence plus model explain the stylized facts of financial time series data? In: Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, Richland, SC, vol. 2, pp. 653–660. IFAAMAS (2012)

    Google Scholar 

  39. Polhill, J.G.: Odd updated. Journal of Artificial Societies and Social Simulation 13(4), 9 (2010)

    MathSciNet  Google Scholar 

  40. Railsback, S., Grimm, V.: Agent-Based and Individual-Based Modeling - A Practical Introduction. Princeton University Press (2012)

    Google Scholar 

  41. Raney, B., Voellmy, A., Çetin, N., Vrtic, M., Nagel, K.: Towards a microscopic traffic simulation of all of switzerland. In: Sloot, P.M.A., Tan, C.J.K., Dongarra, J., Hoekstra, A.G. (eds.) ICCS-ComputSci 2002, Part I. LNCS, vol. 2329, pp. 371–380. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  42. Ricci, A., Piunti, M., Viroli, M.: Environment programming in multi-agent systems: an artifact-based perspective. Autonomous Agents and Multi-Agent Systems 23, 158–192 (2011)

    Article  Google Scholar 

  43. Richiardi, M., Leombruni, R., Saam, N.J., Sonnessa, M.: A common protocol for agent-based social simulation. Journal of Artificial Societies and Social Simulation 9(1), 15 (2006)

    Google Scholar 

  44. Taylor, C.E., Jefferson, D.: Artificial life as a tool for biological inquiry. Artificial Life 1(1-2), 1–14 (1994)

    Google Scholar 

  45. Vincenti, W.G.: What Engineers Know and How They Know it. John Hopkins University Press (1990)

    Google Scholar 

  46. Willemain, T.: Insights on modeling from a dozen experts. Operations Research 42(2), 213–222 (1994)

    Article  Google Scholar 

  47. Wray, R.E., Jones, R.M.: An introduction to Soar as an agent architecture. In: Sun, R. (ed.) Cognition and Multi-agent Interaction: From Cognitive Modeling to Social Simulation, pp. 53–78. Cambridge University Press (2005)

    Google Scholar 

  48. Yilmaz, L., Ören, T.: Agent-Directed Simulation and Systems Engineering. Wiley (2009)

    Google Scholar 

  49. Zeigler, B.P.: Theory of Modeling and Simulation. John-Wiley (1976)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Science and Technology, Örebro University, Örebro, Sweden

    Franziska Klügl

Authors
  1. Franziska Klügl
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institut für Informatik, Technische Universität Clausthal, 38678, Clausthal-Zellerfeld, Germany

    Jörg P. Müller

  2. Istituto di Calcolo e Reti ad Alte Prestazioni, Consiglio Nazionale delle Ricerche, 90128, Palermo, Italy

    Massimo Cossentino

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Klügl, F. (2013). “Engineering” Agent-Based Simulation Models?. In: Müller, J.P., Cossentino, M. (eds) Agent-Oriented Software Engineering XIII. AOSE 2012. Lecture Notes in Computer Science, vol 7852. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39866-7_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39866-7_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39865-0

  • Online ISBN: 978-3-642-39866-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation