Skip to main content

Characterizing Complex Behavior in (Self-organizing) Multi-agent Systems

  • Conference paper
Computational Science and Its Applications – ICCSA 2005 (ICCSA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3481))

Included in the following conference series:

Abstract

In this paper, we show our work on characterizing complex behavior in self-organizing (SOMAS) and non-self-organizing (NonSOMAS) multi-agent systems. Through experiments and analysis, we investigate how Self-Organized Criticality (SOC) phenomena arise in SOMAS rather than in NonSOMAS. Furthermore, we compare the order of agent performance in the two types of systems and explain its implications.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
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. Adami, C.: Self-organized criticality in living systems. Physics Letter A 203, 29–32 (1995)

    Article  Google Scholar 

  2. Albert, R., Jeong, H., Barabasi, A.: Diameter of the world-wide web. Nature 401, 1–30 (1999)

    Article  Google Scholar 

  3. Bak, P.: How Nature Works. Springer, Heidelberg (1996)

    MATH  Google Scholar 

  4. Bak, P., Tang, C., Wiesenfeld, K.: Self-organized criticality. Physical Review A 38(1), 364–374

    Google Scholar 

  5. Barabasi, A., Albert, R.: Emergence of scaling in random networks. Science 286, 509–512 (1999)

    Article  MathSciNet  Google Scholar 

  6. Barabasi, A., Albert, R., Jeong, H.: Scale-free characteristics of random networks: The topology of the world-wide web. Physica A 281, 70–77 (2000)

    Article  Google Scholar 

  7. Chen, M., Dorer, K., Foroughi, E., Heintz, F., Huang, Z.X., Kapetanakis, S., Kostiadis, K., Kummeneje, J., Murray, J., Noda, I., Obst, O., Riley, P., Steffens, T., Wang, Y., Yin, X.: RoboCup server manual. RoboCup Federation (February 2003)

    Google Scholar 

  8. Darley, V.: Emergent phenomena and complexity. Artificial Life (1994)

    Google Scholar 

  9. Hu, B., Liu, J., Jin, X.: From local behaviors to global performance in a multi-agent RoboNBA system. In: IEEE/WIC/ACM Intelligent Agent Technology (IAT 2004), Beijing, pp. 309–314 (2004)

    Google Scholar 

  10. Hu, B., Liu, J., Jin, X.: Multi-agent RoboNBA simulation: From local behaviors to global characteristics. Special Issue: Agent-Directed Simulation of the Simulation: Transactions of the Society for Modeling and Simulation International (2005) (to appear)

    Google Scholar 

  11. Huberman, B., Adamic, L.: Growth dynamics of the world-wide web. Nature 40, 450–457 (1999)

    Google Scholar 

  12. Marcenac, P., Calderoni, S.: Self-organisation in agent-based simulation. In: IREMIA, University of La Runion

    Google Scholar 

  13. Mitchell, M., Newman, M.: Complex systems theory and evolution. Sante Fe Institue Working Paper, 4 (2001)

    Google Scholar 

  14. Parunak, H., Brueckner, S.: Entropy and self-organization in multi-agent systems. In: International Conference on Autonomous Agents (2001)

    Google Scholar 

  15. Parunak, H., Brueckner, S., Fleischer, M., Odell, J.: Co-x: Defining what agents do together. In: Workshop on Team and Coalition Formation, AAMAS 2002, Bologna, Italy (2002)

    Google Scholar 

  16. Reynolds, C.W.: Flocks, herds, and schools: A distributed behavioral In Computer Graphics. In: Proceedings of SIGGRAPH 1987, July 1987, vol. 21(4), pp. 25–34 (1987)

    Google Scholar 

  17. Rosnay, J.: Feedback, http://pespmc1.vub.ac.be/FEED-BACK.html

  18. Sawyer, R.: Simulating emergence and downward causation in small groups. In: Moss, S., Davidsson, P. (eds.) Multi-Agent-based Simulation. Second International Workshop, MABS (2000)

    Google Scholar 

  19. Shiode, N., Batty, M.: Power law distributions in real and virtual worlds. University College London, UK

    Google Scholar 

  20. Sole, R.V., Bonabeau, E., Delgado, J., Fernandez, P., Marin, J.: Pattern formation and optimization in army ant raids. Artificial Life 6, 219–227 (2001)

    Article  Google Scholar 

  21. Valverde, S., Sole, R.: Self-organized critical traffic in parallel computer network. Sante Fe Institue Working Paper (2001)

    Google Scholar 

  22. Zipf, G.: Human Behavior and The Principle of Least Effort. Addison Wesley, Cambridge (1949)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Hu, B., Liu, J. (2005). Characterizing Complex Behavior in (Self-organizing) Multi-agent Systems. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424826_135

Download citation

  • DOI: https://doi.org/10.1007/11424826_135

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25861-2

  • Online ISBN: 978-3-540-32044-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics