Skip to main content

What Can Cellular Automata Tell Us about the Behavior of Large Multi-agent Systems?

  • Conference paper
  • First Online:
Software Engineering for Large-Scale Multi-Agent Systems (SELMAS 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2603))

Abstract

This paper describes the behavior observed in a class of cellular automata that we have defined as “dissipative”, i.e., cellular automata for which the external environment can somehow inject “energy” to dynamically influence the evolution of the automata. In this class of cellular automata, we have observed that stable macro-level global structures emerge from local interactions among cells. Since dissipative cellular automata express characteristics strongly resembling those of open multi-agent systems, we expect that similar sorts of macro-level behaviors are likely to emerge in multiagent systems and need to be studied, controlled, and possibly fruitfully exploited. A preliminary set of experiments reporting two ways of indirectly controlling the behavior of dissipative cellular automata are reported and discussed w.r.t. the possibility of applying similar sort of indirect control on large multi-agent systems.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. R. Albert, H. Jeong, A. Barabasi, “Diameter of the World Wide Web”, Nature, 401:130–131, 9 Sept. 1999.

    Article  Google Scholar 

  2. R. Albert, H. Jeong, A. Barabasi, “Error and Attack Tolerance of Complex Networks”, Nature, 406:378–382, 27 July 2000.

    Article  Google Scholar 

  3. Y. Bar-Yam, Dynamics of Complex systems. Addison-Wesley, 1997.

    Google Scholar 

  4. T. D. Barfoot, G. M. T. D’Eleuterio, “Multiagent Coordination by Stochastic Cellular Automata“, Proceeding of the Joint International Conference on Artificial Intelligence, Seattle (WA), Aug. 2001.

    Google Scholar 

  5. E. Bonabeau, M. Dorigo, G. Theraulaz, Swarm Intelligence. From Natural to Artificial Systems, Santa Fe Institute-Studies in the Science of Complexity. Oxford University Press, 1999.

    Google Scholar 

  6. G. Cabri, L. Leonardi, F. Zambonelli, “Engineering Mobile Agent Applications via Context-Dependent Coordination”, IEEE Transactions on Software Engineering, 28(11), Nov. 2002.

    Google Scholar 

  7. C. V. Goldman, S. Kraus, O. Shehory, “Equilibria Strategies for Selecting Sellers and Satisfying Buyers”, Proc. of the 5th International Workshop on Cooperative Information Agents, LNAI, No. 2182, pp. 166–177, Sept. 2001.

    Google Scholar 

  8. R. Gustavsson, M. Fredriksson, “Coordination and Control in Computational Ecosystems: A Vision of the Future”, in Coordination of Internet Agents, A. Omicini al (Eds.), Springer Verlag, pp. 443–469, 2001.

    Google Scholar 

  9. J.J. Hopfield, “Neural Networks and Physical Systems with Emergent Collective Computational Abilities”, Proc. of the National Academy of Science, 79:2554–2558, 1982.

    Google Scholar 

  10. B. A. Hubermann, T. Hogg, “The Emergence of Computational Ecosystems”, in SFI Studies in the Science of Complexity, Vol. V, Addison-Wesley, 1993.

    Google Scholar 

  11. T. E. Ingerson, R. L. Buvel, “Structure in Asynchronous Cellular Automata”, Physica D, 10:59–68, 1984.

    Article  MathSciNet  Google Scholar 

  12. N. R. Jennings, “On Agent-Based Software Engineering”, Artificial Intelligence, 117(2), 2000.

    Google Scholar 

  13. S. A. Kauffman, The origins of order, Oxford University Press, New York, 1993.

    Google Scholar 

  14. E. D. Lumer, G. Nicolis, “Synchronous Versus Asynchronous Dynamics in Spatially Distributed Systems”, Physica D, 71:440–452, 1994.

    Article  MATH  Google Scholar 

  15. M. Mamei, M. Mahan, “Engineering Mobility in Large Multi-agent Systems”, 2003in this volume.

    Google Scholar 

  16. M. Mamei, L. Leonardi, F. Zambonelli, “Co-Fields: Towards a Unifying Model for Swarm Intelligence”, 3rd International Workshop on Engineering Societies in the Agents’ World, Madrid (E), Sept. 2002.

    Google Scholar 

  17. Y. Moses, M. Tenneholtz, “Artificial Social Systems”, Computers and Artificial Intelligence, 14(3):533–562, 1995.

    MathSciNet  Google Scholar 

  18. G. Nicolis, I. Prigogine, Exploring Complexity: an Introduction, W. H. Freeman, 1989.

    Google Scholar 

  19. V. Parunak, “Go to the Ant: Engineering Principles from Natural Agent Systems”, Annals of Operations Research, 75:69–101, 1997.

    Article  MATH  Google Scholar 

  20. V. Parunak, S. Bruekner, J. Sauter, “ERIM’s Approach to Fine-Grained Agents”, NASA/JPL Workshop on Radical Agent Concepts, Greenbelt (MD), 2002.

    Google Scholar 

  21. M. Ripeani, A. Iamnitchi, I. Foster, “Mapping the Gnutella Network”, IEEE Internet Computing, 6(1):50–57, Jan.–Feb. 2002.

    Article  Google Scholar 

  22. B. Schönfisch, A. De Roos, “Synchronous and Asynchronous Updating in Cellular Automata”, BioSystems, 51(3):123–143, 1999.

    Article  Google Scholar 

  23. M. Sipper. “The Emergence of Cellular Computing”. IEEE Computer, 37(7), July 1999.

    Google Scholar 

  24. D. Tennenhouse, “Proactive Computing”, Communications of the ACM, May 2000.

    Google Scholar 

  25. D. Watts, Small Worlds: The Dynamics of Networks between Order and Randomness, Princeton University Press (Princeton, NJ), 1999.

    Google Scholar 

  26. S. Wolfram, Cellular Automata and Complexity. Addison-Wesley, 1994.

    Google Scholar 

  27. S. Wolfram, A New Kind of Science, Wolfram Media Inc. 2002.

    Google Scholar 

  28. J. T. Wootton, “Local Interactions Predict Large-scale Patterns in Empirically Derived Cellular Automata”, Nature, 413: 841:844, 25 Oct. 2001.

    Article  Google Scholar 

  29. F. Zambonelli, M. Mamei, “The Cloak of Invisibility: Challenges and Applications”, IEEE Pervasive Computing, 1(4):63–72, Oct.–Dec. 2002.

    Article  Google Scholar 

  30. F. Zambonelli, N. R. Jennings, M. J. Wooldridge, “Organizational Abstractions for the Analysis and Design of Multi-agent Systems, 1st Workshop on Agent-Oriented Software Engineering, LNCS No. 1957, Jan. 2001.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Zambonelli, F., Mamei, M., Roli, A. (2003). What Can Cellular Automata Tell Us about the Behavior of Large Multi-agent Systems?. In: Garcia, A., Lucena, C., Zambonelli, F., Omicini, A., Castro, J. (eds) Software Engineering for Large-Scale Multi-Agent Systems. SELMAS 2002. Lecture Notes in Computer Science, vol 2603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-35828-5_14

Download citation

  • DOI: https://doi.org/10.1007/3-540-35828-5_14

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-08772-4

  • Online ISBN: 978-3-540-35828-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics