Skip to main content
SpringerLink
Log in
Book cover

International Symposium on Neural Networks

ISNN 2018: Advances in Neural Networks – ISNN 2018 pp 37–43Cite as

Approaches to Modeling of Nontrivial Cognitive Behavior

  • Conference paper
  • First Online:

  • 3778 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10878))

Abstract

The approaches to modeling of nontrivial cognitive behavior of animals have been analyzed. We consider this modeling in the context of investigation of cognitive evolution. Cognitive evolution is evolution of animal cognitive abilities. The important result of cognitive evolution is the human thinking, which is used in the scientific cognition of nature. The modeling of animal cognitive behavior should be based on the corresponding biological experiments. This paper characterizes briefly the results of biological experiments on cognitive behavior of New Caledonian crows. Schemes of modeling and some results of modeling of cognitive behavior of crows have been characterized. The general relations of our approach with other researches have been also analyzed.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Red’ko, V.G.: Modeling of cognitive evolution: perspective direction of interdisciplinary investigation. Procedia Comput. Sci. 71, 215–220 (2015)

    Article  Google Scholar 

  2. Red’ko, V.G.: Modeling of cognitive evolution: agent-based investigations in cognitive science. In: Cheng, L., Liu, Q., Ronzhin, A. (eds.) ISNN 2016. LNCS, vol. 9719, pp. 720–730. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40663-3_83

    Chapter  Google Scholar 

  3. Red’ko, V.G.: Epistemological foundations of investigation of cognitive evolution. Biol. Inspired Cogn. Archit. 18, 105–115 (2016)

    MathSciNet  Google Scholar 

  4. Turchin, V.F.: The Phenomenon of Science: A Cybernetic Approach to Human Evolution. Columbia University Press, New York (1977)

    Google Scholar 

  5. Taylor, A.H.: Corvid cognition. Wiley Interdisc. Rev.: Cogn. Sci. 5(3), 361–372 (2014)

    Article  Google Scholar 

  6. Weir, A.A.S., Chappell, J., Kacelnik, A.: Shaping of hooks in New Caledonian crows. Science 297(5583), 981–983 (2002)

    Article  Google Scholar 

  7. Taylor, A.H., Elliffe, D., Hunt, G.R., Gray, R.D.: Complex cognition and behavioural innovation in New Caledonian crows. Proc. R. Soc. B. 277(1694), 2637–2643 (2010)

    Article  Google Scholar 

  8. Red’ko, V.G., Burtsev, M.S.: Modeling of mechanism of plan formation by New Caledonian crows. Procedia Comput. Sci. 88, 403–408 (2016). https://www.sciencedirect.com/science/article/pii/S1877050916317124

    Article  Google Scholar 

  9. Anokhin, P.K.: Biology and Neurophysiology of the Conditioned Reflex and its Role in Adaptive Behavior. Pergamon Press, Oxford (1974)

    Google Scholar 

  10. Foster, D.J., Matthew, A., Wilson, M.A.: Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature 440(7084), 680–683 (2006)

    Article  Google Scholar 

  11. Diba, K., Buzsaki, G.: Forward and reverse hippocampal place-cell sequences during ripples. Nat. Neurosci. 10(10), 1241–1242 (2007)

    Article  Google Scholar 

  12. Red’ko, V.G., Anokhin, K.V., Burtsev, M.S., Manolov, A.I., Mosalov, O.P., Nepomnyashchikh, V.A., Prokhorov, D.V.: Project “animat brain”: designing the animat control system on the basis of the functional systems theory. In: Butz, M.V., Sigaud, O., Pezzulo, G., Baldassarre, G. (eds.) ABiALS 2006. LNCS (LNAI), vol. 4520, pp. 94–107. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-74262-3_6. https://www.niisi.ru/iont/ni/rvgpubl/Redkoetal2007.pdf

    Chapter  Google Scholar 

  13. Langley, P., Laird, J.E., Rogers, S.: Cognitive architectures: research issues and challenges. Cogn. Syst. Res. 10(2), 141–160 (2009)

    Article  Google Scholar 

  14. Laird, L.E.: The Soar Cognitive Architecture. The MIT Press, Cambridge (2012)

    Google Scholar 

  15. Website of Soar Research Groups. https://soar.eecs.umich.edu/

  16. Samsonovich, A.V.: On a roadmap for the BICA challenge. Biol. Inspired Cogn. Archit. 1, 100–107 (2012)

    Google Scholar 

  17. Red’ko, V.G.: Principles of functioning of autonomous agent-physicist. In: Chella, A., Pirrone, R., Sorbello, R., Johannsdottir, K.R. (eds.) Biologically Inspired Cognitive Architectures 2012. AISC, vol. 196, pp. 265–266. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34274-5_46

    Chapter  Google Scholar 

Download references

Acknowledgements

This work was carried out within the framework of the state task, project no. 0065-2018-0002. The authors thank anonymous reviewers for useful comments.

Author information

Authors and Affiliations

  1. Scientific Research Institute for System Analysis, Russian Academy of Sciences, Moscow, Russia

    Vladimir G. Red’ko & Galina A. Beskhlebnova

Authors
  1. Vladimir G. Red’ko
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Galina A. Beskhlebnova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vladimir G. Red’ko .

Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Doha, Qatar

    Tingwen Huang

  2. Sichuan University, Chengdu, China

    Jiancheng Lv

  3. Southeast University, Nanjing, China

    Changyin Sun

  4. United Institute of Informatics Problems, Minsk, Belarus

    Alexander V. Tuzikov

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Red’ko, V.G., Beskhlebnova, G.A. (2018). Approaches to Modeling of Nontrivial Cognitive Behavior. In: Huang, T., Lv, J., Sun, C., Tuzikov, A. (eds) Advances in Neural Networks – ISNN 2018. ISNN 2018. Lecture Notes in Computer Science(), vol 10878. Springer, Cham. https://doi.org/10.1007/978-3-319-92537-0_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-92537-0_5

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92536-3

  • Online ISBN: 978-3-319-92537-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation