Keywords
brain neural networks
system synthesis
the Eskov-Zinchenko effect
How to Cite
Abstract
Currently, there is no single definition of artificial intelligence. We need a Such categorization of tasks to be solved by artificial intelligence. The paper proposes a task categorization for artificial neural networks (in terms of obtaining subjectively and objectively new information). The advantages of such neural networks (non-algorithmizable problems) are shown, and a class of systems (third type biosystems) which cannot be studied by statistical methods (and all science) is presented. To study such biosystems (with unique samples) it is suggested to use artificial neural networks able to perform system synthesis (search for order parameters). Nowadays such problems are solved by humans through heuristics, and this process cannot be modeled by the existing artificial intelligence systems.
References
Haken H. Principles of Brain Functioning: a Synergetic Approach to Brain Activity, Behavior and Cognition. Springer Series in Synergetics: Springer; 1995. 349 p.
Miri A., Warriner C. L., Seely J. S., Elsayed G. F., Cunningham J. P., Churchland M. M., Jessell T. M. Behaviorally Selective Engagement of Short-Latency Effector Pathways by Motor Cortex. Neuron. 2017. PMID 28735748. DOI: 10.1016/j.neuron.2017.06.042.
Albert S. T., Hadjiosif A. M., Jang J., Zimnik A. J., Soteropoulos D. S., Baker S. N., Churchland M. M., Krakauer J. W., Shadmehr R. Postural Control of Arm and Fingers Through Integration of Movement Commands. Elife. 2020;9:1-35.
Vokhmina Y. V., Eskov V. M., Gavrilenko T. V., Filatova O. E. Measuring Order Parameters Based on Neural Network Technologies. Measurement Techniques. 2015;58(4):462-466. DOI: 10.1007/S11018-015-0735-X.
Eskov V. V. Mathematical Modeling of Homeostasis and Evolution of Complexity. Tula: TSU Publishing; 2016. 307 p. (In Russ.)
Eskov V. V., Pyatin V. F., Filatova D. Yu. Bashkatova Yu. V. Chaos of Homeostasis Parameters of the Human Cardiovascular System. Samara: Porto-Print Publishing; 2018. 312 p. (In Russ.)
Eskov V. V., Pyatin V. F., Shakirova L. S., Melnikova E. G. The Role of Chaos in the Regulation of Organism Physiological Functions. Samara: Porto-print LLC; 2020. 248 p. (In Russ.)
Eskov V. M., Galkin V. A., Pyatin V. F., Filatov M. A. Control of Movements: Stochastic or Chaos? Samara: Porto-print Publishing; 2020. 144 p. (In Russ.)
Menskii M. B. Concept of Consciousness in the Context of Quantum Mechanics. Physics-Uspekhi. 2005;48(4):389. DOI: 10.3367/UFNr.0175.200504c.0413.
Mensky M. B. Quantum Measurements, the Phenomenon of Life, and Time Arrow: Three Great Problems of Physics (in Ginzburg's Terminology) and Their Interrelation. Physics-Uspekhi. 2007;50(4):397. DOI: 10.3367/UFNr.0177.200704j.0415.
Penrose R. The Emperor's New Mind: Concerning Computers, Mind and Laws of Physics. Oxford University Press; 1989.
Eskov V. M., Gavrilenko T. V., Kozlova V. V., Filatov M. A. Measurement of the Dynamic Parameters of Microchaos in the Behavior of Living Biosystems. Measurement Techniques. 2012;55(9):1096-1101. DOI: 10.1007/S11018-012-0082-0.
Eskov V. M., Gavrilenko T. V., Vokhmina Y. V., Zimin M. I., Filatov M. A. Measurement of Chaotic Dynamics for Two Types of Tapping as Voluntary Movements. Measurement Techniques. 2014;57(6):720-724. DOI: 10.1007/S11018-014-0525-X.
Eskov V. V., Filatova D. Y., Ilyashenko L. K., Vochmina Y. V. Classification of Uncertainties in Modeling of Complex Biological Systems. Moscow University Physics Bulletin. 2019;74(1):57-63. DOI: 10.3103/S0027134919010089.
Eskov V. M., Eskov V. V., Vochmina Y. V., Gorbunov D. V., Ilyashenko L. K. Shannon Entropy in the Research on Stationary Regimes and the Evolution of Complexity. Moscow University Physics Bulletin. 2017;72(3):309-317. DOI: 10.3103/S0027134917030067.
Zilov V. G., Khadartsev A. A., Eskov V. V., Ilyashenko L. K., Kitanina K. Yu. Examination of Statistical Instability of Electroencephalograms. Bulletin of Experimental Biology and Medicine. 2019;168(7):5-9. DOI: 10.1007/s10517-019-04633-7.
Filatova O. E. Standardizing Measurements of the Parameters of Mathematical Models of Neural Networks. Measurement Techniques. 1997;40(1):55-59. DOI: 10.1007/BF02505166.
Weaver W. Science and Complexity. American Scientist. 1948;36:536-544.
Kauffman S. A. The Origins of Order: Self-Organization and Selection in Evolution. Oxford: Oxford University Press; 1993.
Kelso J. S. Dynamic Patterns: the Self-Organization of Brain and Behavior. Cambridge, MA: MIT Press; 1995.
Eskov V. M., Pyatin V. F., Bashkatova Y. V. Medical and Biological Cybernetics: Perspectives of Development. Russian Journal of Cybernetics. 2020;1(1):58-67.
Khadartsev A. A., Filatova O. E., Mandryka I. A., Eskov V. V. The Entropy-Based Approach to Physics of Living Systems and the Chaos and Self-Organization Theory. Russian Journal of Cybernetics. 2020;1(3):41-49.
Tomasello M. A Natural History of Human Thinking. Cambridge, M.A.: Harvard University Press; 2014.
Hill A. V. Why Biophysics? Science. 1956;124(3234):1233-1237.
Eskov V. M., Pyatin V. F., Eskov V. V., Ilyashenko L. K. Heuristic Work of the Brain and Artificial Neural Networks. Biophysics. 2019;64(2):293-299. DOI: 10.1134/S0006350919020064.
Zilov V. G., Khadartsev A. A., Ilyashenko L. K., Eskov V. V., Minenko I. A. Experimental Analysis of the Chaotic Dynamics of Muscle Biopotentials under Various Static Loads. Bulletin of Experimental Biology and Medicine. 2018;165(4):415-418. DOI: 10.1007/s10517-018-4183-x.
Kolosova A. I., Filatov M. A., Maistrenko E. V., Ilyashenko L. K. An Analysis of the Attention Indices in Students from Surgut and Samara Oblast From the Standpoint of Stochastics and Chaos. Biophysics. 2019;64(4):662-666. DOI: 10.1134/S0006350919040067.
Pyatin V. F., Eskov V. V. Can Homeostasis Be Static? Russian Journal of Cybernetics. 2021;2(1):26-34.
Eskov V. V. Modeling of Biosystems from the Stand Point of “Complexity” by W. Weaver and “Fuzziness” by L. A. Zadeh. Journal of Physics Conference Series. 2021;1889(5):052020. DOI: 10.1088/1742-6596/1889/5/052020.
Eskov V. M., Filatova O. E., Ivashenko V. P. Computer Identification of Compartmental Neuron Circuits. Measurement Techniques. 1994;37(8):967-971. DOI: 10.1007/BF01418921.
Galkin V. A. Analysis of Mathematical Models: Systems of Conservation Laws, Boltzmann and Smoluchowski Equations. M.: BINOM. Laboratoriya znanii; 2009. 408 p. (In Russ.)
Filatova O. E., Bazhenova A. E., Ilyashenko L. K., Grigorieva S. V. Estimation of the Parameters for Tremograms According to the Eskov–Zinchenko Effect. Biophysics. 2018:63(2):262-267. DOI: 10.1134/S0006350918020082.
Filatova O. E., Berestin D. K., Ilyashenko L. K., Bashkatova Yu. V. The Influence of Hypothermia on the Parameters of the Electromyogram at Low Muscle Tone State. Human Ecology. 2019;5:43-48. DOI: 10.33396/1728-0869-2019-5-43-48.
Filatova O. E. Measurement and Control Facilities for Investigating Neuron Systems. Measurement Techniques. 1998;41(3):229-232. DOI: 10.1007/BF02503888.
Galkin V. A., Eskov V. V., Pyatin V. F., Kirasirova L. A., Kulchitsky V. A. Is There Stochastic Sample Stability in Neurosciences? News of Biomedical Sciences. 2020;20(3):126-132.
Eskov V. V., Bashkatova Yu. V., Shakirova L. S., Vedeneeva T.S., Mordvintseva A. Yu. Problem of Standard in Medicine and Physiology. Archives of Clinical and Experimental Medicine. 2020;29(3):211-216.
Filatova O. E., Bashkatova Yu. V., Shakirova L. S., Filatov M. A. Neural Network Technologies in System Synthesis. IOP Conf. Series: Materials Science and Engineering. 2021;1047:012099. DOI: 10.1088/1757-899X/1047/1/012099.
Grigorenko V. V., Bashkatova Yu. V., Shakirova L. S., Egorov A. A., Nazina N. B. New Information Technologies in the Estimation of Stationary Modes of the Third Type Systems. IOP Conference Series: Materials Science and Engineering. 2020;862:052034. DOI: 10.1088/1757-899X/862/5/052034.
Grigorenko V. V., Nazina N. B., Filatov M. A., Chempalova L. S., Tretyakov S. A. New Information Technologies in the Estimation of the Third Type Systems. Journal of Physics: Conference Series. 2021;1889:032003. DOI: 10.1088/1742-6596/1889/3/032003.