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Unlearning Phenomena in Co-evolution of Non-uniform Cellular Automata

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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 results of a study of a genetic algorithm, designed to evolve cellular automata for solving a given problem. Evolution is performed between the cell’s update-rules in a local manner, allowing for easy parallelization. As a case study, the algorithm was applied to the density classification problem: classifying any given initial configuration according to the percentage of 1-valued cells. The main result presented in this paper is an ’unlearning’ phenomenon: highly fit solutions are generated by the algorithm, only to be ’unlearned’ and completely disappear as the evolutionary run continues.

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References

  1. von Neumann, J.: Theory of Self Reproducing Automata. University of Illinois Press, Illinois (1966); Edited and completed by A.W. Burks

    Google Scholar 

  2. Mitchell, M., Crutcheld, J.P., Hraber, P.T.: Evolving cellular automata to perform computations: Mechanisms and impediments. Physica D 75, 361–391 (1994)

    Article  MATH  Google Scholar 

  3. Mitchell, M., Hraber, P.T., Crutcheld, J.P.: Revisiting the edge of chaos: Evolving cellular automata to perform computations. Complex Systems 7, 89–130 (1993)

    MATH  Google Scholar 

  4. Sloot, P.M.A., Kaandorp, J.A., Hoekstra, A.G., Overeinder, B.J.: Distributed Cellular Automata: Large Scale Simulation of Natural Phenomena. In: Zomaya, A.Y., Ercal, F., Olariu, S. (eds.) Solutions to Parallel and Distributed Computing Problems: Lessons from Biological Sciences, pp. 1–46. Computer Centre University of Tromso (2001)

    Google Scholar 

  5. Crutchfield, J.P., Mitchell, M., Das, R.: The Evolutionary Design of Collective Computation in Cellular Automata, http://www.santafe.edu/sfi/publications/wpabstract/199809080

  6. Sipper, M.: Co-evolving non-uniform cellular automata to perform computations. Physica D 92, 193–208 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  7. Sipper, M., Tomassini, M.: Computation in artificially evolved, non-uniform cellular automata. Theoretical Computer Science 217, 81–98 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  8. Sipper, M.: Evolution of Parallel Cellular Programming Approach. LNCS. Springer, Heidelberg ISBN - 3-540-62613-1

    Google Scholar 

  9. Pettey, C.C.: Diffusion (Cellular) Models. In: The Handbook of Evolutionary Computation. Oxford University Press, Oxford (1997)

    Google Scholar 

  10. Land, M., Belew, R.K.: No Perfect Two-State Cellular Automata for Density Classification Exists. Physical Review Letters, 74(25), June 19 (1995)

    Google Scholar 

  11. Wainwright, R.T.: Life is universal! In: Proceedings of the 7th Conference on Winter simulation, Washington, DC, vol. 2, pp. 449–459 (1974)

    Google Scholar 

  12. Schoneveld, A., de Ronde, J.F., Sloot, P.M.A., Kaandorp, J.A.: A Parallel Cellular Genetic Algorithm Used in Finite Element Simulation. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol. 1141, pp. 533–542. Springer, Heidelberg (1996)

    Chapter  Google Scholar 

  13. Sloot, P.M.A., Schoneveld, A., de Ronde, J.F., Kaandorp, J.A.: Large scale simulations of complex systems Part I: conceptual framework (SFI Working Paper: 97-07-070) Santa Fe Instute for Complex studies (1997)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Leskes, B., Sloot, P.M.A. (2004). Unlearning Phenomena in Co-evolution of Non-uniform Cellular Automata. 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_18

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  • DOI: https://doi.org/10.1007/978-3-540-30479-1_18

  • 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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