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A Novel Artificial Life Ecosystem Environment Model

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Cellular Automata (ACRI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3305))

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Abstract

This paper presents information flow model and a novel artificial life grid model to construct artificial life computer ecosystem environment. The life grid model is a three-dimensional information space: (time, artificial life node, and location). The former two dimensions identify the contents or function of artificial life systems, and the third-dimension identifies the location where an artificial life system exists. We depart the artificial life node architecture into four levels: artificial life system application level, engine library level, sensor level, and the connectivity level. In information flow model, we present the ALife information definition, characteristic and four kinds of information communication mechanisms (broad-diffuse, Multi-diffuse, uni-diffuse and any-diffuse).

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References

  1. Langton, C.G.: Artificial life. In: Langton, C.G. (ed.) Artificial life SFI studies in the sciences of complexity, vol. VI. Addison-Wesley, Reading (1989)

    Google Scholar 

  2. von Neumann, J.: Theory of self-Reproducing automata. University Illinois Presses, Urbana

    Google Scholar 

  3. Langton, C.G.: Life at the edge of chaos. In: Langton, V.G., Taylor, E., Farmer, J.D., Rasmussen, S. (eds.) Artificial life II. SFI studies in the sciences of complexity, vol. x. Addison-Wesley, Reading

    Google Scholar 

  4. Wolfram, S.: Theory and application of cellular automata. World Scientific, Singapore (1986)

    Google Scholar 

  5. Lindenmayer, A., Prusinkiewicz, P.: Developmental models of multicellular organisms. In: Langton, C.G. (ed.) Artificial life. SFI studies in the sciences of complexity, vol. VI. Addison-Wesley, Reading (1989)

    Google Scholar 

  6. Dawkins, R.: The evolution of Evolvability. In: Langton, C.G. (ed.) Artificial life. SFI studies in the sciences of complexity, vol. VI. Addison-Wesley, Reading (1989)

    Google Scholar 

  7. Holland, J.: Adaptation in natural and artificial systems. University of Michigan Press, Ann arbor (1975)

    Google Scholar 

  8. Goldberg, D.E.: Gentic algorithms in search, Optimization and Machine learning. Addison-Wesley, Reading (1989)

    Google Scholar 

  9. Eigen, M., Schuster, P.: The hypercycle: A principle of natureal self-organization. Springer, New York (1979)

    Google Scholar 

  10. Baglev, R., Farmer, J.F.: Emergence of Robust autocatalytic network. In: Langton, C.G., Taylor, C.E., Farmer, J.D., Rasmussen, S. (eds.) Artificial life II. SFI studies in the sciences of complexity, vol. X. Addison-Wesley, Reading (1991)

    Google Scholar 

  11. North, G.: Expanding the RNA repetrtoire. Naturen 345 (1990)

    Google Scholar 

  12. Zeleny, M.: Precepiation membrances, Osmotic Growths and Synthetic Biology. In: Langton, C.G. (ed.) Artificial life. SFI studies in the sciences of complexity, vol. VI. Addison-Wesley, Reading (1989)

    Google Scholar 

  13. Schrodinger, E.: What is life? Cambridge University Press, Cambridge (1994)

    Google Scholar 

  14. Deneubourg, J.L., Gross, S.: Collective Patterns and Deciscion making. Ethology Ecology & Evolution 1 (1989)

    Google Scholar 

  15. Ray, T.S.: An approach to the synthesis of life. In: langton, C.G., taylor, C.E., Rasmussen, S. (eds.) Artificial life II. SFI studies in the sciences of complexity, vol. X. Addison-Wesley, Reading (1991)

    Google Scholar 

  16. Spafford, E.H.: Computer Virus, A Form of artificial life? In: Langton, C.G., Rasmussen, S. (eds.) Artificial life 77. SFI studies in the science of complexity, vol. X. Addison Wesley, Reading (1991)

    Google Scholar 

  17. Wildberger, M.: Introduction & Overview of “Artificial Life” Evolving Intelligent Agents for Modeling & Simulation. In: Charnes, J.M., Morrice, D.J., Brunner, D.T., Swmn, J.J. (eds.) Proceedings of the 1996 Winter Simulation Conference (1996)

    Google Scholar 

  18. Bates, J.: The role of emotion in believable agents. Commun. ACM 37(7), 122–125 (1994)

    Article  Google Scholar 

  19. Steels, L.: Evolving grounded communication for robots. TRENDS in Cognitive Sciences 7(7) (July 2003)

    Google Scholar 

  20. Neocleous, C., Schizas, C.: Artificial Neural Network Learning: A Comparative Review. In: Vlahavas, I.P., Spyropoulos, C.D. (eds.) SETN 2002. LNCS (LNAI), vol. 2308, pp. 300–313. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  21. Funge, J., Tu, X., Terzopoulos, D.: Cognitive modeling: Knowledge, reasoning, and planning for intelligent characters. In: Proceedings of SIGGRAPH 1999, Los Angeles, August 8–13 (1999); Funge, J.: Representing knowledge within the situation calculus using IVE fluents. J. Reliable Comput. 5(1), 35–61 (1999)

    Google Scholar 

  22. Funge, J.: AI for Games and Animation: A Cognitive Modeling Approach. A.K. Peters, Stanford (1999)

    Google Scholar 

  23. Foster, I., Kesselman, C., Nick, J.M., Tuecke, S.: An Open Grid Services Architecture for Distributed Systems integration, www.globus.org/research/papers/ogsa.pdf

  24. Heflin, J.: A portrait of the semantic web in action, vol. 16(2) (2001)

    Google Scholar 

  25. Zhuge, H.: A Knowledge Flow Model for Peer-to-Peer Team Knowledge Sharing and Management. Expert Systems with Applications 23, 23–30 (2002)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of computer, NanJing University of Aeronautics and Astronautics, China

    Zhengyou Xia

  2. Department of Computing information & technology, Fudan University, China

    Yichuan Jiang

Authors
  1. Zhengyou Xia
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  2. Yichuan Jiang
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Editor information

Editors and Affiliations

  1. Faculty of Sciences, Section of Computational Science, University of Amsterdam, Kruislaan 403, 1098 SJ, Amsterdam, The Netherlands

    Peter M. A. Sloot

  2. Computer Science Department, University of Geneva, Switzerland

    Bastien Chopard

  3. Section Computational Science, University of Amsterdam, The Netherlands

    Alfons G. Hoekstra

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© 2004 Springer-Verlag Berlin Heidelberg

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Xia, Z., Jiang, Y. (2004). A Novel Artificial Life Ecosystem Environment Model. In: Sloot, P.M.A., Chopard, B., Hoekstra, A.G. (eds) Cellular Automata. ACRI 2004. Lecture Notes in Computer Science, vol 3305. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30479-1_67

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  • DOI: https://doi.org/10.1007/978-3-540-30479-1_67

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23596-5

  • Online ISBN: 978-3-540-30479-1

  • eBook Packages: Springer Book Archive

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