Dynamical theory of information as a basis for natural-constructive approach to modeling a cognitive process

 pdf (601K)  / Annotation

List of references:

  1. Википедиа [Электронный Ресурс]. https: //en.wikipedia.org/wiki/Main_Page.
  2. А. А. Жданов. Автономный искусственный интеллект. — М: БИНОМ, 2015.
    • A. A. Zhdanov. Autonomous Artificial Intelligence. — Moscow: BINOM, 2015. — in Russian.
  3. А. Г. Колупаев, Д. С. Чернавский. Перемешивающий слой // Краткие сообщения по физике. 1997. — Т. 1, № 2. — С. 12–18.
    • A. G. Kolupaev, D. S. Chernavskii. Mixing layer // Short reports on physics. 1997. — V. 1, no. 2. — P. 12–18. — in Russian.
  4. Цифровая библиотека по философии [Электронный ресурс]. http://filosof.historic.ru/enc/item/f00/s10/a001041.shtml.
  5. О. Д. Чернавская, Д. С. Чернавский. Естественно-конструктивистский подход к моделированию мышления // Биофизика. 2016. — Т. 61, № 1. — С. 185–200.
    • O. D. Chernavskaya, D. S. Chernavskii. Estesstvenno-konstructivistskii podhod k modelirovaniyu myshleniya // Biofizika. 2016. — V. 61, no. 1. — P. 185–200. — in Russian.
    • O. D. Chernavskaya, D. S. Chernavskii. Natural-Constructive Approach to modeling the Cognitive Process // Biophysics. 2016. — V. 61, no. 1. — P. 155–169. — DOI: 10.1134/S0006350916010061.
  6. О. Д. Чернавская, Д. С. Чернавский, В. П. Карп, А. П. Никитин, Д. С. Щепетов. О подходе к процессу моделирования мышления с позиций динамической теории информации / Подходы к моделированию мышления: Сборник. Под ред. В. Г. Редько. — М: ЛЕНАНД, 2014.
    • O. D. Chernavskaya, D. S. Chernavskii, V. P. Karp, A. P. Nikitin, D. S. Schepetov. On the approach to modeling the cognitive process from the viewpoint of dynamical theory of information / Approaches to modeling the cognitive process. Ed. V. G. Red’ko. — Moscow: LENAND, 2014.
  7. Д. С. Чернавский. Синергетика и информация. Динамическая Теория Информации. — М: Едиториал УРСС, 2004.
    • D. S. Chernavskii. Synergetics and Information: Dynamical Theory of Information. — Moscow: Editorial URSS, 2004. — in Russian. — MathSciNet: MR1893136.
  8. А. Л. Шамис. Пути моделирования мышления. — М: КомКнига, 2006.
    • A. L. Shamis. The ways of thinking modeling. — Moscow: Komkniga, 2006. — in Russian.
  9. O. D. Chernavskaya, D. S. Chernavskii, V. P. Karp, A. P. Nikitin, D. S. Shchepetov. An architecture of thinking system within the Dynamical Theory of Information // Biologically Inspired Cognitive Architecture. 2013. — V. 6. — P. 147–158. — DOI: 10.1016/j.bica.2013.05.013.
  10. O. D. Chernavskaya, D. S. Chernavskii, V. P. Karp, A. P. Nikitin, Shchepetov D. S.. ., Rozylo Ya. A. An architecture of the cognitive system with account for emotional component // Biologically Inspired Cognitive Architecture. 2015. — V. 12. — P. 144–154. — DOI: 10.1016/j.bica.2015.04.009.
  11. O. D. Chernavskaya, Ya. A. Rozhylo. The Natural-Constructive Approach to Representation of Emotions and a Sense of Humor in an Artificial Cognitive System // IARIA Journal of Life Sciences. 2016. — V. 8, no. 3&4. — P. 184–202.
  12. T. W. Deacon. The symbolic species: the co-evolution of langufage and the brain. — N. Y: Norton, 1997.
  13. K. Doya. Complementary roles of basal ganglia and cerebellum in learning and motor control // Current Opinion in Neurobiology. 2000. — V. 10. — P. 732–739. — DOI: 10.1016/S0959-4388(00)00153-7.
  14. R. FitzHugh. Impulses and physiological states in theoretical models of nerve membrane // Biophys J. 1961. — V. 1. — P. 445. — DOI: 10.1016/S0006-3495(61)86902-6.
  15. E. Goldberg. The new executive brain. — Oxford University Press, 2009.
  16. S. Grossberg. Studies of Mind and Brain. — Boston: Riedel, 1982. — MathSciNet: MR0667852.
  17. H. Haken. Information and Self-Organization: A macro-scopic approach to complex systems. — Springer, 2000. — MathSciNet: MR1735498.
  18. D. O. Hebb. The organization of behavior. — John Wiley & Sons, 1949.
  19. A. L. Hodgkin, A. F. Huxley. A quantitative description of membrane current and its application to conduction and excitation in nerve // The Journal of physiology. 1963. — V. 117. — P. 500–544. — DOI: 10.1113/jphysiol.1952.sp004764.
  20. J. J. Hopfield. Neural networks and physical systems with emergent collective computational abilities // Proceedings of the national academy of sciences (PNAS). 1982. — V. 79. — P. 2554. — DOI: 10.1073/pnas.79.8.2554. — MathSciNet: MR0652033.
  21. E. M. Izhikevich. Dynamical systems in neuroscience: the geometry of excitability and bursting. — MIT Press, 2007. — MathSciNet: MR2263523.
  22. E. M. Izhikevich, G. M. Edelman. Large-scale model of mammalian thalamocortical systems // Proceedings of the national academy of sciences (PNAS). 2008. — V. 105. — P. 9. — DOI: 10.1073/pnas.0712231105.
  23. I. Kant. Critick of Rure Reason. — London: William Pickering, 1838.
  24. T. Kohonen. Self-Organizing Maps. — Springer, 2001. — MathSciNet: MR1844512.
  25. L. F. Koziol, D. E. Budding. Subcortical Structures and Cognition: Implications for Neurophysiological Assessment. — Springer, 2009.
  26. J. E. Laird. The Soar cognitive architecture. — MIT Press, 2012.
  27. Y. LeCun, Y. Bengio, G. Hinton. Deep Learning // Nature. 2015. — V. 521. — P. 436–444. — DOI: 10.1038/nature14539. — MathSciNet: MR3342741.
  28. J. Levin. Materialism and Qualia: The Explanatory Gap // Pacific Philosophical Quarterly. 1983. — V. 64, no. 4. — P. 354–361. — DOI: 10.1111/j.1468-0114.1983.tb00207.x.
  29. J. Nagumo, S. Arimoto, S. Yashizawa. An active pulse transmission line simulating nerve axon // Procedings of IRE. 1962. — V. 50. — P. 2062.
  30. J. Panksepp, L. Biven. The Archaeology of Mind: Neuroevolutionary Origins of Human Emotions. — N. Y: Norton, 2012.
  31. R. Penrose. Shadows of the Mind. — Oxford University Press, 1994. — MathSciNet: MR1865778.
  32. I. Prigogine. End of Certainty. — The Free Press, 1997.
  33. H. Quastler. The emergence of biological organization. — New Haven: Yale University Press, 1964.
  34. A. Samsonovich. Bringing consciousness to cognitive neuroscience: a computational perspective // Journal of Integrated Design and Process Science. 2007. — V. 1. — P. 19–30.
  35. O. E. Svarnik, K. V. Anokhin, Yu. I. Aleksandrov. Experience of a First Whisker-Dependent Skill Affects: the Induction of c-Fos Expression in Somatosensory Cortex Barrel Field Neurons in Rats on Training the Second Skill // Neuroscience and Behavioral Physiology. 2015. — V. 45. — P. 724. — DOI: 10.1007/s11055-015-0135-3.
  36. A. M. Turing. Computing machinery and intelligence // Mind. 1950. — V. 59. — P. 433–460. — DOI: 10.1093/mind/LIX.236.433. — MathSciNet: MR0037064.
  37. P. Vershure. The Distributed Adaptive Control: A theory of the mind, brain, body nexus // Biologically Inspired Cognitive Architecture. 2012. — V. 1. — P. 55–72. — DOI: 10.1016/j.bica.2012.04.005.
  38. W. Weaver, C. Shannon. The Mathematical Theory of Communication. — Univ. of Illinois Press, 1963. — MathSciNet: MR0032134.
  39. N. Wiener. Cybernetics: Or Control and Communication in the Animal and the Machine. — MIT Press, 1948. — MathSciNet: MR0025096.

Indexed in Scopus

Full-text version of the journal is also available on the web site of the scientific electronic library eLIBRARY.RU

The journal is included in the Russian Science Citation Index

The journal is included in the RSCI

International Interdisciplinary Conference "Mathematics. Computing. Education"