Journal Neurocomputers №4 for 2021 г.
Article in number:
Art is realized by neural networks and organized by interaction of systemic immunoelements with space
Type of article: scientific article
DOI: 10.18127/j19998554-202104-05
UDC: 004.8;681.5;24-183.4
Authors:

N.V. Panov1, I.B. Komkov2, A.V. Savelyev3, N.A. Loginova4

1,4 Institute of Highest Nervous Activity and Neurophysiology of RAS (Moscow, Russia); 

2 Sports Club «KANKU» (Troitsk, Moscow Region, Russia);

3 Patent agency «©Uniquely honest patenting» (Moscow, Russia); VMZ at the Military Register SDS (Moscow, Russia)

Abstract:

The possibility of acquiring and transferring properties through interaction with space is solved in the martial arts of the East (MAE) using the multi-level logic of the system of restrictions. A creative approach to MAE solves the main problem associated with the formation of an individual's personality, and spatial-plane interaction can provide the perception of the required parameters of the system. Therefore, MAE is not only necessary for world art as the latest viable system, but also serves as the foundation for the creation of artificial intelligence (AI).

The aim of the research was to analyze the meaning of MAE for art; to show the possibility of obtaining ways of acquiring and transferring properties in art with the aim of consciously influencing recipients.

For any kind of art from the point of view of Nikritin's tectonics, which is based on the organizational science of A.A. Bogdanov (tectology) are characterized by universal principles that can be identified in every art. The martial arts of the East (for example, karate) have all the characteristics inherent in art and creativity in general, in which principles can be distinguished that allow them to be combined and actively used in various combinations.

The practical use of approaches typical for MAE is possible taking into account the work of feedback, which is based on the possibility of constructing immunized movements, which are important for robotics, including AI, since they do not allow deviations from a given trajectory or assigned tasks.

Pages: 50-62
For citation

Panov N.V., Komkov I.B., Savelyev A.V., Loginova N.A. Art is realized by neural networks and organized by interaction of systemic immunoelements with space. Neurocomputers. 2021. V. 23. № 4. Р. 50−62. DOI: https://doi.org/10.18127/j19998554-202104-05  (in Russian).

References
  1. Pushkarev A.V. Tvorchestvo i iskusstvennyj intellect: postanovka problemy. Gumanitarnye, social’no-ekonomicheskie i obschestvennye nauki. 2014. № 12-1. S. 93-96 (in Russian).
  2. Gatys L.A., Ecker A.S., Bethge M. A neural algorithm of artistic style. Computer Science. 2015. arXiv: 1508.06576 3. Audry S., Ippolito J. Can artificial intelligence make art without artists? Ask the viewer. Arts. 2019. V. 8(1). Article 35.
  3. Hong J.-W., Curran N.M. Artificial intelligence, artists, and art: attitudes toward artwork produced by humans vs. artificial intelligence. ACM Transactions on multimedia computing, communications, and applications. 2019. V. 15. Iss. 25. Article 58. P. 1-16.
  4. Kim P. Convolutional neural network. In: MATLAB Deep Learning. Apress, Berkeley, CA, 2017. P. 121–147. DOI: https://doi.org/10.1007/978-1-4842-2845-6_6
  5. Ouyang X., Zhou P., Li C.H., Liu L. Sentiment analysis using convolutional neural network. IEEE International conference. 2015. DOI: 10.1109/CIT/IUCC/DASC/PICOM.2015.349
  6. Zhang Y., Pardo B.A., Duan Z. Siamese style convolutional neural networks for sound search by vocal imitation. IEEE/ACM Transactions on audio speech and language processing. 2019. V. 27. Iss. 2. P. 429–441.
  7. Bogdanov A.A. Tektologiya. M.: Akademicheskiy Proyekt. Triksta. 2019. 712 s (in Russian).
  8. Pchelkina L.R. Solomon Nikritin – khudozhnik i teoretik. K voprosu o razrabotke Tektonicheskogo issledovaniya zhivopisi. Iskusstvoznaniye. 2014. № 3-4. S. 342–355 (in Russian).
  9. Pchelkina L.R. Biomekhanika dvizheniya i zvuka v Proyektsionnom teatre Solomona Nikritina. Teatr. Zhivopis. Kino. Muzyka. 2014. № 1. S. 105–129 (in Russian).
  10. Blinova E.K. Vospriyatiye ordernykh kompozitsiy kak postroyeniye modeley prostranstv. Izvestiya Rossiyskogo gosu-darstvennogo pedagogicheskogo universiteta im. A.I. Gertsena. 2008. S. 92–104 (in Russian).
  11. Panov N.V., Komkov I.B., Savelyev A.V., Kositsyn N.S., Loginova N.A. Prostranstvenno-ploskostnoye vzaimodeystviye soznaniya s vneshnim mirom v neyrolokomotorike boyevykh iskusstv Vostoka dlya razrabotki robotizirovannykh sistem printsipialno novogo tipa – gumanoidnogo immunoandroida kak tekhnoimmunosistemy. Neyrokompyutery: razrabotka. primeneniye. 2019. T. 21. № 4. S. 58–66 (in Russian).
  12. Osipov G.S., Velichkovskiy B.M. ISKUSSTVENNYY INTELLEKT. Bolshaya Rossiyskaya entsiklopediya. Elektronnaya versiya (2016); https://bigenc.ru/mathematics/text/2022537 Data obrashcheniya: 25.06.2020 (in Russian).
  13. Kalmykov V.V. Myshleniye i iskusstvennyy intellekt. Vestnik Mordovskogo universiteta. 2008. № 3. S. 31–33 (in Russian).
  14. Goldberg A.P. Sistema dlya polucheniya tvorcheskogo iskusstvennogo intellekta. Patent na izobreteniye RU 2 092 900 C1 (data publikatsii: 10.10.1997) (in Russian).
  15. Gaydenko P.P., Leontyev D.A.     TVORChESTVO.      Bolshaya Rossiyskaya            entsiklopediya.       Elektronnaya           versiya    (2017); https://bigenc.ru/philosophy/text/4184848 Data obrashcheniya: 25.06.2020 (in Russian).
  16. Romashko S.A. ISKUSSTVO. Bolshaya Rossiyskaya entsiklopediya. Elektronnaya versiya (2016); https://bigenc.ru/philosophy/text/2022615 Data obrashcheniya: 25.06.2020 (in Russian).
  17. Panov N.V., Komkov I.B., Savelyev A.V., Loginova N.A. Organizacionnaya teoriya raspredeleniya elementov soznaniya i informacionnotekhnicheskiy immunitet sistemy boevykh iskusstv Vostoka. Neyrokompyutery: razrabotka. primeneniye. 2021. T. 23. № 2. S. 43–54 (in Russian).
  18. Fedulov M.V., Panov N.V., Loginova N.A., Kositsyn N.S. Ispolzovaniye iskusstvenno vvodimykh soznaniyem cheloveka pravil postroyeniya dvizheniy dlya povysheniya effektivnosti boyevykh iskusstv. Neyrokompyutery: razrabotka. primeneniye. 2016. № 12. S. 77–84 (in Russian).
  19. Fedulov M.V., Panov N.V., Loginova N.A., Kositsyn N.S. Logicheskaya regulyatsiya dvizheniy i analiz sovmestimosti sistem na primere tkhekvondo i karate. Neyrokompyutery: razrabotka. primeneniye. 2017. № 5. S. 36–38 (in Russian).
  20. Fedulov M.V., Panov N.V., Loginova N.A., Savelyev A.V., Kositsyn N.S. Ispolzovaniye neyrolokomotornykh prin-tsipov postroyeniya dvizheniy na primere boyevykh iskusstv. Neyrokompyutery: razrabotka. primeneniye. 2017. № 8. S. 41–43 (in Russian).
  21. Fedulov M.V., Panov N.V., Loginova N.A., Garakh Zh.V., Komkov I.B., Savelyev A.V., Kositsyn N.S. Neyrolokomotor-nyye printsipy kak osnova kognitivnogo podkhoda k postroyeniyu dvizheniy v boyevykh iskusstvakh i robototekhnike. Neyrokompyutery: razrabotka. primeneniye. 2018. № 5. S. 36–41 (in Russian).
Date of receipt: 13.05.2021
Approved after review: 27.05.2021
Accepted for publication: 28.06.2021