Skip to main content

On the Complex Behaviour of Natural and Artificial Machines and Systems

Part of the Cognitive Systems Monographs book series (COSMOS,volume 36)

Abstract

One of the most important aims of the fields of robotics, artificial intelligence and artificial life is the design and construction of systems and machines as versatile and as reliable as living organisms at performing high level human-like tasks. But how are we to evaluate artificial systems if we are not certain how to measure these capacities in living systems, let alone how to define life or intelligence? Here I survey a concrete metric towards measuring abstract properties of natural and artificial systems, such as the ability to react to the environment and to control one’s own behaviour.

Keywords

  • Natural computing
  • Systems’ behaviour
  • Controllability
  • Programmability
  • Turing test
  • Compressibility
  • Kolmogorov complexity
  • Randomness
  • Robotics
  • Artificial life

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-14126-4_6
  • Chapter length: 15 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   119.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-14126-4
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   159.99
Price excludes VAT (USA)
Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

References

  1. Zenil, H., Gershenson, C., Marshall, J.A.R., Rosenblueth, D.: Life as thermodynamic evidence of algorithmic structure in natural environments. Entropy 14(11), 2173–2191 (2012)

    MathSciNet  CrossRef  Google Scholar 

  2. Ciresan, D.C., Meier, U., Masci, J., Schmidhuber, J.: Multi-column deep neural network for traffic sign classification. Neural Netw. 32, 333–338 (2012)

    CrossRef  Google Scholar 

  3. Wolfram, S.: A New Kind of Science. Wolfram Media (2002)

    Google Scholar 

  4. Cook, M.: Universality in elementary cellular automata. Complex Syst. 15, 1–40 (2004)

    MathSciNet  MATH  Google Scholar 

  5. Zenil, H.: Compression-based investigation of the behaviour of cellular automata and other systems. Complex Syst. 19(2) (2010)

    Google Scholar 

  6. Perlis, A.J.: Epigrams on programming. SIGPLAN Not. 17(9), 7–13 (1982)

    CrossRef  Google Scholar 

  7. Cronin, L., Krasnogor, N., Davis, B.G., Alexander, C., Robertson, N., Steinke, J.H.G., Schroeder, S.L.M., Khlobystov, A.N., Cooper, G., Gardner, P.M., Siepmann, P., Whitaker, B.J., Marsh, D.: The imitation game—a computational chemical approach to recognizing life. Nat. Biotechnol. 24, 1203–1206 (2006)

    Google Scholar 

  8. Zenil, H., Ball, G., Tegnér, J.: Testing biological models for non-linear sensitivity with a programmability test. In: Liò, P., Miglino, O., Nicosia, G., Nolfi, S., Pavone, M. (eds.) Advances in Artificial Intelligence, ECAL 2013, pp. 1222–1223. MIT Press, Cambridge (2013). https://doi.org/10.7551/978-0-262-31719-2-ch188

  9. Maier, R., Zimmer, R., Kü ffner, R.: A Turing test for artificial expression data. Bioinformatics 29(20), 2603–2609 (2013)

    Google Scholar 

  10. Zenil, H.: What is nature-like computation? A behavioural approach and a notion of programmability. Philos. Technol. (2012). https://doi.org/10.1007/s13347-012-0095-2

    CrossRef  Google Scholar 

  11. Zenil, H.: A turing test-inspired approach to natural computation. In: Primiero, G., De Mol, L. (eds.) Turing in Context II, Historical and Contemporary Research in Logic, Computing Machinery and Artificial Intelligence. Proceedings by the Royal Flemish Academy of Belgium for Science and the Arts, Belgium (2013)

    Google Scholar 

  12. Osawa, H., Tobita, K., Kuwayama, Y., Imai, M., Yamada, S.: Behavioral turing test using two-axis actuators. In: IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication (2012)

    Google Scholar 

  13. Chaitin, G.J.: On the length of programs for computing finite binary sequences: statistical considerations. J. ACM 16(1), 145–159 (1969)

    MathSciNet  CrossRef  Google Scholar 

  14. Kolmogorov, A.N.: Three approaches to the quantitative definition of information. Probl. Inf. Trans. 1(1), 1–7 (1965)

    MathSciNet  Google Scholar 

  15. Delahaye, J.-P., Zenil, H.: Numerical evaluation of the complexity of short strings: a glance into the innermost structure of algorithmic randomness. Appl. Math. Comput. 219, 63–77 (2012)

    MATH  Google Scholar 

  16. Soler-Toscano, F., Zenil, H., Delahaye, J.-P., Gauvrit, N.: Calculating Kolmogorov complexity from the output frequency distributions of small turing machines. PLoS ONE 9(5), e96223 (2014)

    CrossRef  Google Scholar 

  17. Zenil, H.: On the dynamic qualitative behaviour of universal computation. Complex Syst. 20(3) (2012)

    Google Scholar 

  18. Zenil, H.: Programmability for natural computation and the game of life as a case study. J. Exp. Theor. Artif. Intell. https://doi.org/10.1080/0952813X.2014.940686 (in press)

  19. Floridi, L.: Enveloping the world: risks and opportunities in the development of increasingly smart technologies. CONNECT (ed.), 03 Jun 2011. http://ec.europa.eu/digital-agenda/en/blog/enveloping-the-world-risks-and-opportunities-in-the-development-of-increasingly-smart-technologies. Accessed 15 July 2014

  20. Prokopenko, X., Gerasimov, V., Tanev, I.: Measuring spatiotemporal coordination in a modular robotic system. In: Proceedings of Artificial Life X (2006)

    Google Scholar 

  21. Levin, L.: Laws of information conservation (non-growth) and aspects of the foundation of probability theory. Probl. Inf. Trans. 10(3), 206–210 (1974)

    Google Scholar 

  22. Terrazas, G., Zenil, H., Krasnogor, N.: Exploring programmable self-assembly in non DNA-based computing. Nat. Comput. 12(4), 499–515 (2013)

    MathSciNet  CrossRef  Google Scholar 

  23. Gauvrit, N., Zenil, H., Soler-Toscano, F., Delahaye, J.-P.: Algorithmic complexity for short binary strings applied to psychology: a primer, Behavior Research Methods, 6 Dec 2013 (epub ahead of print)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. Zenil .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Verify currency and authenticity via CrossMark

Cite this chapter

Zenil, H. (2020). On the Complex Behaviour of Natural and Artificial Machines and Systems. In: Bonsignorio, F., Messina, E., del Pobil, A., Hallam, J. (eds) Metrics of Sensory Motor Coordination and Integration in Robots and Animals. Cognitive Systems Monographs, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-030-14126-4_6

Download citation