Measuring Complexity of Multi-agent Simulations – An Attempt Using Metrics

  • Franziska Klügl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5118)

Abstract

The variety of existing agent-based simulations is overwhelming. However – especially when comparing agent-based simulation to other simulation paradigms, a reference frame is missing that allows characterizing shortly and discriminating between simulation models. In this contribution, I address this problem by introducing metrics for measuring properties of agent-based simulations for finally being able to characterize the complexities involved in developing such a model.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [Axelrod, 1995]
    Axelrod, R.: A model of the emergence of new political actors. In: Gilbert, N., Conte, R. (eds.) Artificial Societies: The Computer Simulation of Social Life, p. 19. UCL Press (1995)Google Scholar
  2. [Briand et al., 1997]
    Briand, L., Devanbu, P., Melo, W.: An investigation into coupling measures for C++. In: Proceedings of the 1997 (19th) International Conference on Software Engineering, pp. 412–421 (1997)Google Scholar
  3. [Bülow, 2005]
    Bülow, M.: Metriken für Multiagentensimulationen in SeSAm. Master’s thesis, Institute of Computer Science, University of Würzburg (2005)Google Scholar
  4. [Chen and Suen, 1994]
    Chen, Z., Suen, C.Y.: Complexity metrics for rule-based expert systems. In: International Conference on Software Maintenance, 1994, pp. 382–391 (1994)Google Scholar
  5. [Chidamber and Kemerer, 1994]
    Chidamber, S.R., Kemerer, C.F.: A metrics suite for object oriented design. IEEE Trans. Software Engineering 20, 476–493 (1994)CrossRefGoogle Scholar
  6. [Conde et al., 1986]
    Conde, S.D., Dunsmore, H.E., Shen, V.Y.: Software Engineering Metrics and Models. Benjamin/Cummings (1986)Google Scholar
  7. [Dumke et al., 2000]
    Dumke, R.R., Koeppe, R., Wille, C.: Software agent measurement and self-measuring agent-based systems. Technical Report 11, Fakultät für Informatik, Uni. Madgeburg (2000)Google Scholar
  8. [Epstein and Axtell, 1996]
    Epstein, J.M., Axtell, R.: Growing Artificial Societies. Social Science from the Bottom Up. Random House Uk Ltd. (1996)Google Scholar
  9. [Far and Wanyama, 2003]
    Far, B.H., Wanyama, T.: Metrics for agent-based software development. In: IEEE CCECE 2003. Canadian Conference on Electrical and Computer Engineering, May 2003, vol. 2, pp. 1297–1300 (2003)Google Scholar
  10. [Firby, 1989]
    Firby, J.: Adaptive Execution in Complex Dynamic Worlds. PhD thesis, Yale University (1989)Google Scholar
  11. [Forrester, 1961]
    Forrester, J.: Industrial Dynamics. Pegasus Communications (1961)Google Scholar
  12. [Gómes-Sanz et al., 2006]
    Gómes-Sanz, J.J., Pavón, J., Garijo, F.: Estimating cost for agent-oriented software. In: Müller, J., Zambonelli, F. (eds.) AOSE 2005. LNCS, vol. 3950, pp. 218–230. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  13. [Holland, 2000]
    Holland, J.H.: Emergence. From Chaos to Order. Oxford University Press, Oxford (2000)Google Scholar
  14. [Ingrand et al., 1992]
    Ingrand, F.F., Georgeff, M.P., Rao, A.S.: An architecture for real-time reasoning and system control. IEEE Expert 7(6), 34–44 (1992)CrossRefGoogle Scholar
  15. [Klügl, 2001]
    Klügl, F.: Multiagentensimulation – Konzepte, Anwendungen, Tools. Addision Wesley (2001)Google Scholar
  16. [Klügl et al., 2005]
    Klügl, F., Fehler, M., Herrler, R.: About the role of the environment in multi-agent simulations. In: Weyns, D., Parunak, H.V.D., Michel, F. (eds.) E4MAS 2004. LNCS (LNAI), vol. 3374, pp. 127–149. Springer, Heidelberg (2005)Google Scholar
  17. [Klügl et al., 2004]
    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
  18. [Klügl and Rindsfüser, 2007]
    Klügl, F., Rindsfüser, G.: Large-scale agent-based pedestrian simulation. In: Müller, J.P., Petta, P., Klusch, M., Georgeff, M. (eds.) MATES 2007. LNCS (LNAI), vol. 4687, pp. 145–156. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  19. [Robby et al., 2006]
    Robby, DeLoach, S.A., Kolesnikov, V.A.: Using design metrics for predicting system flexibility. In: Baresi, L., Heckel, R. (eds.) FASE 2006. LNCS, vol. 3922, pp. 184–198. Springer, Heidelberg (2006)Google Scholar
  20. [Thaller, 2000]
    Thaller, G.E.: Software-Metriken – einsetzen, bewerten, messen, 2nd edn. Verlag Technik (2000)Google Scholar
  21. [Uhrmacher, 1996]
    Uhrmacher, A.M.: Object-oriented and agent-oriented simulation-implications for social science applications. In: Doran, J., Gilbert, N., Müller, U., Troitzsch, K.G. (eds.) Social Science Micro Simulation- A Challenge for Computer Science. Lecture Notes in Economics and Mathematics, pp. 432–447. Springer, Berlin (1996)Google Scholar
  22. [Wallace, 1987]
    Wallace, J.C.: The control and transformation metric: Toward the measurement of simulation model complexity. In: Thesen, A., Grant, H., Kelton, W.D. (eds.) Proceedings of the 1987 Winter Simulation Conference, pp. 597–603 (1987)Google Scholar
  23. [Wille et al., 2004]
    Wille, C., Brehmer, N., Dumke, R.R.: Software measurement of agent-based systems - an evaluation study of the agent academy. Technical Report Preprint No. 3, Faculty of Informatics, University of Magdeburg (2004)Google Scholar
  24. [Woodside, 2001]
    Woodside, M.: Scalability metrics and analysis of mobile agent systems. In: Wagner, T.A., Rana, O.F. (eds.) AA-WS 2000. LNCS (LNAI), vol. 1887, p. 234. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  25. [Wooldridge, 2002]
    Wooldridge, M.: An Introduction to Multi-Agent Systems. John Wiley, Chichester (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Franziska Klügl
    • 1
  1. 1.Department for Artificial IntelligenceUniversity of WürzburgWürzburg 

Personalised recommendations