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The Cognitive Architecture Within the Natural-Constructive Approach

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Biologically Inspired Cognitive Architectures (BICA) for Young Scientists

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 449))

Abstract

The cognitive architecture designed within the natural-constructive approach to modeling the cognitive process is presented. This approach is based on the dynamical theory of information, the neurophysiology data, and neural computing (using the concept of dynamical formal neuron). It is shown that this architecture enables us to interpret and reproduce peculiar features of the human cognitive process, namely—uncertainty, individuality, intuitive and logical thinking, etc. It is shown that the human emotions could be interpreted as the derivative of the noise amplitude, with the absolute value reflects the degree of emotional reaction, while its sign corresponds to negative or positive emotion, respectively; thereby wide spread binary classification gets natural explanation.

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Author information

Authors and Affiliations

  1. P. N. Lebedev Physical Institute, Russian Academy of Sciences, Moscow, Russia

    Olga Chernavskaya

Authors
  1. Olga Chernavskaya
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Correspondence to Olga Chernavskaya .

Editor information

Editors and Affiliations

  1. Department 22 “Cybernetics”, National Research Nuclear University, Moscow, Russia

    Alexei V. Samsonovich

  2. “MEPhI”, National Research Nuclear University, Moscow, Russia

    Valentin V. Klimov

  3. “MEPhI”, National Research Nuclear University, Moscow, Russia

    Galina V. Rybina

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Chernavskaya, O. (2016). The Cognitive Architecture Within the Natural-Constructive Approach. In: Samsonovich, A., Klimov, V., Rybina, G. (eds) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists . Advances in Intelligent Systems and Computing, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-319-32554-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-32554-5_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32553-8

  • Online ISBN: 978-3-319-32554-5

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