Skip to main content

On the Identification of \(\alpha \)-Asynchronous Cellular Automata in the Case of Partial Observations with Spatially Separated Gaps

  • Chapter
  • First Online:
Challenging Problems and Solutions in Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 634))

Abstract

In this paper we present a statistical method, based on frequencies, for identifying so-called \(\alpha \)-asynchronous Cellular Automata from partial observations, i.e. pre-recorded configurations of the system with some cells having an unknown (missing) state. The presented method, in addition to finding the unknown Cellular Automaton, is able to unveil the missing state values with high accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Adamatzky, A.: Identification of Cellular Automata. Taylor & Francis Group, London (1994)

    MATH  Google Scholar 

  2. Al-Kheder, S., Wang, J., Shan, J.: Cellular automata urban growth model calibration with genetic algorithms. In: Urban Remote Sensing Joint Event, pp. 1–5. IEEE Press (2007)

    Google Scholar 

  3. Andre, D., Bennett, III, F.H., Koza, J.R.: Discovery by genetic programming of a cellular automata rule that is better than any known rule for the majority classification problem. In: Proceedings of the 1st Annual Conference on Genetic Programming, pp. 3–11. MIT Press, Cambridge (1996)

    Google Scholar 

  4. Baetens, J.M., Van der Weeën, P., De Baets, B.: Effect of asynchronous updating on the stability of cellular automata. Chaos Solitons Fractals 45, 383–394 (2012)

    Article  MATH  Google Scholar 

  5. Bandini, S., Manzoni, S., Vanneschi, L.: Evolving robust cellular automata rules with genetic programming. In: Adamatzky, A., Alonso-Sanz, R., Lawniczak, A.T., Martínez, G.J., Morita, K., Worsch, T. (eds.) Automata, pp. 542–556. Luniver Press, Frome (2008)

    Google Scholar 

  6. Billings, S.A., Yang, Y.: Identification of probabilistic cellular automata. IEEE Trans. Syst. Man Cybern. Part B Cybern. 33, 225–236 (2003)

    Article  Google Scholar 

  7. Bołt, W., Baetens, J.M., De Baets, B.: Identifying CAs with evolutionary algorithms. In: Proceedings of the 19th International Workshop on Cellular Automata and Discrete Complex Systems (AUTOMATA 2013) - Exploratory Papers, pp. 11–20 (2013)

    Google Scholar 

  8. Bołt, W., Baetens, J.M., De Baets, B.: An evolutionary approach to the identification of cellular automata based on partial observations. In: Proceedings of the 2015 Congress of Evolutionary Computation (CEC 2015). IEEE Press (2015)

    Google Scholar 

  9. Brown, L.D., Cai, T.T., DasGupta, A.: Interval estimation for a binomial proportion. Stat. Sci. 16(2), 101–133 (2001)

    MathSciNet  MATH  Google Scholar 

  10. Bull, L., Adamatzky, A.: A learning classifier system approach to the identification of cellular automata. J. Cell. Autom. 2, 21–38 (2007)

    MathSciNet  MATH  Google Scholar 

  11. Bäck, T., Breukelaar, R., Willmes, L.: Inverse design of cellular automata by genetic algorithms: an unconventional programming paradigm. In: Banâtre, J.P., Fradet, P., Giavitto, J.L., Michel, O. (eds.) Unconventional Programming Paradigms. Lecture Notes in Computer Science, vol. 3566, pp. 161–172. Springer, Berlin (2005)

    Chapter  Google Scholar 

  12. Das, D.: A survey on cellular automata and its applications. In: Krishna, P., Babu, M., Ariwa, E. (eds.) Global Trends in Computing and Communication Systems, Communications in Computer and Information Science, vol. 269, pp. 753–762. Springer, Berlin (2012)

    Google Scholar 

  13. Fatès, N.: A guided tour of asynchronous cellular automata. In: Kari, J., Kutrib, M., Malcher, A. (eds.) Cellular Automata and Discrete Complex Systems. Lecture Notes in Computer Science, vol. 8155, pp. 15–30. Springer, Berlin (2013)

    Chapter  Google Scholar 

  14. Fatès, N., Morvan, M.: An experimental study of robustness to asynchronism for elementary cellular automata. Complex Syst. 16, 1–27 (2005)

    MathSciNet  MATH  Google Scholar 

  15. Ferreira, C.: Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence, Studies in Computational Intelligence, vol. 21. Springer, Berlin (2006)

    MATH  Google Scholar 

  16. Liu, X., Li, X., Liu, L., He, J., Ai, B.: A bottom-up approach to discover transition rules of cellular automata using ant intelligence. Int. J. Geogr. Inf. Sci. 22, 1247–1269 (2008)

    Article  Google Scholar 

  17. Maeda, K., Sakama, C.: Identifying cellular automata rules. J. Cell. Autom. 2, 1–20 (2007)

    MathSciNet  MATH  Google Scholar 

  18. Mitchell, M., Crutchfield, J.P., Das, R.: Evolving cellular automata with genetic algorithms: a review of recent work. In: Proceedings of the First International Conference on Evolutionary Computation and its Applications (EvCA’96) (1996)

    Google Scholar 

  19. Richards, F.C., Meyer, T.P., Packard, N.H.: Extracting cellular automaton rules directly from experimental data. Phys. D: Nonlinear Phenom. 45, 189–202 (1990)

    Article  MATH  Google Scholar 

  20. Rosin, P.L.: Image processing using 3-state cellular automata. Comput. Vis. Image Underst. 114, 790–802 (2010)

    Article  Google Scholar 

  21. Sapin, E., Bull, L., Adamatzky, A.: Genetic approaches to search for computing patterns in cellular automata. Comput. Intell. Mag. 4, 20–28 (2009)

    Article  Google Scholar 

  22. Sapin, E., Bailleux, O., Chabrier, J.J.: Research of a cellular automaton simulating logic gates by evolutionary algorithms. In: Proceedings of the 6th European Conference on Genetic Programming, EuroGP’03, pp. 414–423. Springer, Berlin (2003)

    Google Scholar 

  23. Schönfisch, B., de Roos, A.: Synchronous and asynchronous updating in cellular automata. Biosyst. 51, 123–143 (1999)

    Article  Google Scholar 

  24. Sun, X., Rosin, P.L., Martin, R.R.: Fast rule identification and neighborhood selection for cellular automata. IEEE Trans. Syst. Man Cybern. Part B: Cybern 41, 749–760 (2011)

    Article  Google Scholar 

  25. Wolfram, S.: Statistical mechanics of cellular automata. Rev. Mod. Phys. 55, 601–644 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  26. Yang, Y., Billings, S.A.: Neighborhood detection and rule selection from cellular automata patterns. IEEE Trans. Syst. Man Cybern. Part A: Syst. Hum. 30, 840–847 (2000)

    Article  Google Scholar 

  27. Yang, Y., Billings, S.A.: Extracting Boolean rules from CA patterns. IEEE Trans. Syst. Man Cybern. Part B: Cybern. 30, 573–580 (2000)

    Article  Google Scholar 

Download references

Acknowledgments

Witold Bołt is supported by the Foundation for Polish Science under International PhD Projects in Intelligent Computing. This project is financed by the European Union within the Innovative Economy Operational Program 2007–2013 and the European Regional Development Fund.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Witold Bołt .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Bołt, W., Wolnik, B., Baetens, J.M., De Baets, B. (2016). On the Identification of \(\alpha \)-Asynchronous Cellular Automata in the Case of Partial Observations with Spatially Separated Gaps. In: Trė, G., Grzegorzewski, P., Kacprzyk, J., Owsiński, J., Penczek, W., Zadrożny, S. (eds) Challenging Problems and Solutions in Intelligent Systems. Studies in Computational Intelligence, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-30165-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30165-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30164-8

  • Online ISBN: 978-3-319-30165-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics