Cell Dormancy in Cellular Automata

  • Mohammad Ali Javaheri Javid
  • Rene te Boekhorst
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3993)


This paper describes a novel implementation of a two-dimensional Cellular Automaton (CA) by introducing a dormant state. An overview of the use of CA’s in the field of Artificial Life reveals that certain crucial aspects of biological realism have been sacrificed in favour of abstraction or have not been considered at all. Conway’s famous “Game of Life” model includes certain fundamental aspects of population dynamics, including the transition from living state to dead state. But even the simplest biological system consists of more stages than the binary state in the Game of Life. The aim of this research is to build an extended CA model of natural biological systems by introducing a dormant state and to investigate the effect of dormancy on simple population dynamics.


Cellular Automaton Artificial Life Dormant State Dormant Cell Binary State 
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  1. 1.
    Langton, C.G., Shimohara, K.: Artificial Life V: Proceedings of the Fifth International Workshop on the Synthesis and Simulation of Living systems. The MIT Press/A Bradford Book (1996)Google Scholar
  2. 2.
    Langton, C.G.: Artificial Life. In: Langton, C.G. (ed.) Artificial Life, pp. 1–47. Addison-Wesley, Reading (1989)Google Scholar
  3. 3.
    von Neumann, J.: Theory of Self-Reproducing Automata, University of Illinois Press, Illinois. Edited and completed by A. W. Burks (1996)Google Scholar
  4. 4.
    Flake, G.W.: The computational beauty of Nature. MIT press, Cambridge (1998)zbMATHGoogle Scholar
  5. 5.
    Nehaniv, C.L.: Evolution in asynchronous cellular automata. In: Proceedings of the eighth international conference on artificial life, pp. 65–73 (2002)Google Scholar
  6. 6.
    Wolfram, S.: Universality and complexity in cellular automata. Physica D 10, 1–35 (1984)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Tofoli, T., Margolus, N.: Cellular Automata Machines. The MIT Press, Cambridge (1987)Google Scholar
  8. 8.
    Gardner, M.: The fantastic combinations of John Conway’s new solitaire game “Life”. Sci. Am. 223, 120–123 (1970)CrossRefGoogle Scholar
  9. 9.
    Charles, T., David, J.: Artificial life as a tool for biological inquiry. In: Langton, C.G. (ed.) Artificial Life: an overview, pp. 1–14. MIT Press, Cambridge (1995)Google Scholar
  10. 10.
    Ray, T.S.: Artificial Life. In: Dulbecco, R., Baltimore, D., Jacob, F., Levi-Montalcini, R. (eds.) Frontiers of Life, One The Origins of Life, vol. 1, pp. 107–124. Academic Press, London (2001)Google Scholar
  11. 11.
    Emmeche, C.: The Garden in the Machine. Princeton (1994)Google Scholar
  12. 12.
    Adami, C.: Introduction to Artificial Life. Springer, Berlin (1998)zbMATHGoogle Scholar
  13. 13.
    Heins, Y.: Survival and Dormancy of Microorganism. John Wiley & Sons, Chichester (1987)Google Scholar
  14. 14.
    Roszak, D.B., Colwell, R.R.: Survival strategies of bacteria in the natural environments. Am. J. Pub. Health 51, 365–379 (1987)Google Scholar
  15. 15.
    Barer, M.R., Harwood, C.R.: Bacterial viability and culturability. Adv. Microb. Physiol. 41, 93–137 (1999)CrossRefGoogle Scholar
  16. 16.
    Heudin, J.C.: Virtual Worlds. In: Heudin, J.-C. (ed.) VW 1998. LNCS (LNAI), vol. 1434. Springer, Heidelberg (1998)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Mohammad Ali Javaheri Javid
    • 1
  • Rene te Boekhorst
    • 1
  1. 1.School of Computer Science, Faculty of Engineering and Information SciencesUniversity of HertfordshireHatfield, HertfordshireUnited Kingdom

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