Advertisement

Evolving Multi-agent Networks in Structured Environments

  • T. Glotzmann
  • H. Lange
  • M. Hauhs
  • A. Lamm
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2159)

Abstract

A crucial feature of evolving natural systems is parallelism. The simultaneous and distributed application of rules (governed by e.g. biochemistry) is generally considered as the preposition to build up complex structures. In this article, the potential of agent-based modelling equipped with a concurrent rewriting rule system for artificial evolution is investigated. The task given to the system (pattern construction drawing from a small pool of symbols) is sequential in character, but has to be solved by a strictly parallel rule system. This requires special care in setting up the environment, and it turns out that this is accomplished only by virtue of a hierarchy of levels and modularisation. The proposed three level hierarchy resembles stages of natural evolution in which the emergence of stabilizing mechanisms and cooperative behaviour can be studied. A few preliminary simlation runs are shown and discussed.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J.P. Banatre and D. Le Metayer (1995): Gamma and the chemical reaction model. In: Proceedings of the Coordination’95 workshop. IC Press, London.Google Scholar
  2. Boudol, G. and Berry, G. (1992): The chemical abstract machine. Theoretical Computer Science 96, 217–248.Google Scholar
  3. Bedau, M. A., Snyder, E. and Packard, N.H. (1998): A Classification of Long-Term Evolutionary Dynamics. In: Adami, C., Belew, R.K., Kitano, H. and Taylor, C.E. (eds.), Artificial Life VI. MIT Press, CambridgeGoogle Scholar
  4. Csuhaj-Varjú, E., Kelemen, J., Kelemenová, A. and Paun, G. (1997): Eco-Grammar Systems: A Grammatical Framework for Studying Lifelike Interactions. Artificial Life 3, 1–28.Google Scholar
  5. Goldberg, D.E. (1989): Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley: Reading.Google Scholar
  6. May, R.M. (1974): Stability and complexity in model ecosystems. Princeton Univ. Press.Google Scholar
  7. Milner, R. (1989): Communication and Concurrency. Prentice Hall, Hertfordshire.zbMATHGoogle Scholar
  8. Meseguer, José (1996): Rewriting Logic as a Semantic Framework for Concurrency: a Progress Report, SRI International.Google Scholar
  9. Meseguer, José (1998): Research Directions in Rewriting Logic, In: U. Berger and H. Schwichtenberg, editors, Computational Logic, NATO Advanced Study, Institute, Marktoberdorf, Germany, July 29–August 6, 1997. Springer-Verlag.Google Scholar
  10. Oaks, S., Wong, H. (1999): Java Threads, O’Reilly, Beijing.Google Scholar
  11. Prusinkiewicz, P. and Lindenmayer, A. (1990): The Algorithmic Beauty of Plants. Springer, New York.zbMATHGoogle Scholar
  12. Speroni, P., Dittrich, P. and Banzhaf, W. (2001): Towards a Theory of Organizations. In: Lange, H. (ed.): Proceedings of the 4th German Workshop on Artificial Life. Bayreuther Forum Ökologie (in press).Google Scholar
  13. Suzuki, Y., Tsumoto, S. and Tanaka, H. (1997): Analysis of Cycles in Symbolic Chemical System based on Abstract Rewriting System on Multisets. Artificial Life V, 522–528. MIT press.Google Scholar
  14. Wegner, P. and Goldin, D. (2000): Coinductive Models of Finite Computing Agents. Electronic Notes in Theoretical Computer Science 19, 21.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • T. Glotzmann
    • 1
  • H. Lange
    • 1
  • M. Hauhs
    • 1
  • A. Lamm
    • 1
  1. 1.BITÖKUniversity of BayreuthIsrael

Personalised recommendations