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Ассоциация нейроинформатики
Конференция НЕЙРОИНФОРМАТИКА
Журналы:
Нейроинформатика
Optical Memory and Neural Networks
Vladimir G. Red'ko

 

Doctor of Science (Physics and Mathematics), PhD,
Deputy Director of Center of Optical Neural Technologies, Scientific Research Institute for System Analysis, Russian Academy of Sciences, Moscow, Russia

Research Interests:
Problem of origin of human intelligence, Evolution of animal cognition abilities, Modeling of cognitive evolution

Biographical Sketch
Selected Publications
Homepage in Russian
Old Homepage at Keldysh Institute of Applied Mathematics

Address: Scientific Research Institute for System Analysis of the Russian Academy of Sciences, Nakhimovskiy pr., 36-1, Moscow, 117218, Russia
E-mail: vgredko_at_gmail.com
Tel.: +7 (499) 135-13-51
Fax: +7 (499) 135-13-51

Biographical Sketch:

Vladimir G. Red'ko graduated from Moscow Institute of Physics and Technology in 1971. He received Ph.D. (from Moscow Institute of Physics and Technology) and Doctor of Science (from State Research and Development Institute of Physical Problems) degrees in 1978 and 1995, respectively.

In 1971-1995 V.G. Red'ko worked in several industrial Research and Development Institutes. During that work, Red'ko theoretically investigated the dynamics of magnetic domain walls and vertical Bloch lines, as well as the physical basis of magnetic microelectronic devices.

Since 1979 Red'ko turned his scientific interests to the problem: "Why and how did highly organized biological information systems arise through evolution?" He has developed several mathematical models describing biocybernetic properties at very early stages of biological evolution. Spin-glass model of evolution and Adaptive syser (the model of control origin at prebiological level) are examples of these models.

Currently, V.G. Red'ko develops approaches to modeling of cognitive evolution. Modeling of cognitive evolution is a study of evolution of animal cognitive properties by means of mathematical and computer models. The important result of cognitive evolution is human thinking that is used at scientific cognition.

Selected Publications

  • Red'ko V.G. Epistemological foundations of investigation of cognitive evolution // Biologically Inspired Cognitive Architectures. 2016. Vol. 18. P. 105-115. DOI: 10.1016/j.bica.2016.10.001
  • Red'ko V.G., Burtsev M.S. Modeling of mechanism of plan formation by New Caledonian crows // Procedia Computer Science. 2016. Vol. 88. P. 403-408. See also: http://www.sciencedirect.com/science/article/pii/S1877050916317124. DOI: 10.1016/j.procs.2016.07.456
  • Red'ko V.G., Sharipova T.I., Beskhlebnova G.A. Modeling of searching agent behavior by means of neural gas // Procedia Computer Science. 2016. Vol. 88. P. 409-414. See also: http://www.sciencedirect.com/science/article/pii/S1877050916317136. DOI: 10.1016/j.procs.2016.07.457
  • Red'ko V.G. Modeling of cognitive evolution: Agent-based investigations in cognitive science // In: Long Cheng L., Liu Q., Ronzhin A. (Eds.). Advances in Neural Networks - ISNN 2016. 13th International Symposium on Neural Networks, ISNN 2016, St. Petersburg, Russia, July 6-8, 2016, Proceedings, LNCS 9719. PP. 720-730. Springer International Publishing Switzerland, 2016. DOI: 10.1007/978-3-319-40663-3_83
  • Red'ko V.G. Models of autonomous cognitive agents // In: Samsonovich A.V., Klimov V.V., Rybina G.V. (Eds.). Biologically Inspired Cognitive Architectures (BICA) for Young Scientists. Proceedings of the First International Early Research Career Enhancement School (FIERCES 2016). 2016, pp. 9-15. Springer International Publishing Switzerland, 2016. DOI: 10.1007/978-3-319-32554-5_2
  • Sokhova Z.B., Red'ko V.G. Agent-based model of interactions in the community of investors and producers // In: Samsonovich A.V., Klimov V.V., Rybina G.V. (eds.) Biologically Inspired Cognitive Architectures (BICA) for Young Scientists. Proceedings of the First International Early Research Career Enhancement School (FIERCES 2016). 2016, pp. 235-240. Springer International Publishing Switzerland, 2016. DOI: 10.1007/978-3-319-32554-5_30
  • Red'ko V.G. Modeling of Cognitive Evolution: Toward A Theory of the Evolutionary Origin of Thinking. Moscow: URSS, 2015 (Book in Russian).
  • Red'ko V.G. Modeling of cognitive evolution: perspective direction of interdisciplinary investigation // Procedia Computer Science. 2015. Vol. 71. PP. 215-220. See also: http://www.sciencedirect.com/science/article/pii/S1877050915036686.
  • Red'ko V.G., Nepomnyashchikh V.A. Model of plan formation by New Caledonian crows // Procedia Computer Science. 2015. Vol. 71. PP. 248-253. See also: http://www.sciencedirect.com/science/article/pii/S1877050915036820.
  • Red'ko V.G., Nepomnyashchikh V.A., Osipova E.A. Models of fish exploratory behavior in mazes // Biologically Inspired Cognitive Architectures. 2015. Vol. 13. PP. 9-16. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redkoetal2015.pdf.
  • Red'ko V.G. The Model of Interaction between Learning and Evolutionary Optimization // Mathematical Biology and Bioinformatics. 2014. Vol. 9. No. 2. PP. t1-t15. See also: http://www.matbio.org/2012/Redko_9_t1.pdf.
  • Red'ko V.G.. Model of Interaction between Learning and Evolution // In Cornell University Library Archive (http://arxiv.org/): See also: http://arxiv.org/abs/1411.5053.
  • Red'ko V.G. Interaction between learning and evolution in populations of autonomous agents // International Journal of Computing. 2013. V. 12. No. 1. PP. 42-47. See also: http://www.computingonline.net/index.php/computing/article/view/586/548.
  • Red'ko V.G. Optimization of autonomous agents by means of learning and evolution // Biologically Inspired Cognitive Architectures. 2013. Vol. 6. PP. 18-22. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redko2013.pdf.
  • Red'ko V.G. Principles of functioning of autonomous agent-physicist // Biologically Inspired Cognitive Architectures 2012. Proceedings of the Third Annual Meeting of the BICA Society (A. Chella, R. Pirrone, R. Sorbello, K.R. Johannsdottir, Eds). Springer: Heidelberg, New York, Dordrecht, London. PP. 265-266. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redko2012.pdf.
  • Red'ko V.G. Approaches to modeling of cognitive evolution // International Journal of Computing, 2011. V. 10. No. 1. PP. 33-41. See also: http://www.computingonline.net/index.php/computing/article/view/734/695.
  • Nepomnyashchikh V.A., Popov E.E., Red'ko V.G. A bionic model of adaptive searching behavior // Journal of Computer and System Sciences International. 2008. Vol. 47. No. 1. PP.78-85.
  • Nepomnyashchikh V.A., Popov E.E., Red'ko V.G. Biologically inspired model of adaptive searching behavior // Optical Memory and Neural Networks (Information Optics), 2008, Vol. 17, No. 1, pp. 69-74. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Nepomnetal20082.pdf.
  • 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.), Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior. LNAI 4520, Berlin, Heidelberg: Springer Verlag. 2007. PP. 94-107. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redkoetal2007.pdf.
  • Red'ko V.G. The natural way to artificial intelligence // In B. Goertzel, C. Pennachin (Eds.), Artificial General Intelligence. Springer. Berlin, Heidelberg, New York. 2007. PP. 327-351. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redko2007.pdf.
  • Red'ko, V.G. Evolution, Neural Networks, Intelligence: Models and Conceptions of Evolutionary Cybernetics. Moscow: URSS, 2005. (Book in Russian).
  • Red'ko, V. G., and Tsoy, Yu. R. Estimation of the efficiency of evolution algorithms // Doklady Mathematics. 2005. Vol. 72 No. 2. PP. 810-813.
  • Red'ko V.G., Mosalov O.P., Prokhorov D.V. A model of evolution and learning // Neural Networks. 2005. Vol. 18. No 5-6. PP. 738-745. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redkoetal2005.pdf
  • Red'ko V.G., Prokhorov D.V., Burtsev M.S. Theory of functional systems, adaptive critics and neural networks // International Joint Conference on Neural Networks, Proceedings. Budapest, 2004. PP. 1787-1792.
  • Red'ko V.G. Modeling cognitive evolution: the natural way towards artificial intelligence // Optical Memory and Neural Networks. 2003. Vol. 12. No.3. PP. 219-226. See also: http:/www.niisi.ru/iont/ni/rvgpubl/Redko2003.pdf.
  • Burtsev M.S., Gusarev R.V., Red'ko V.G. Investigation of mechanisms of goal-oriented adaptive control // Journal of Computer and System Sciences International, 2002. Vol. 41. No. 6. PP. 890-897.
  • Red'ko V.G. Evolutionary cybernetics. Moscow: Nauka, 2001 (Book in Russian).
  • Red'ko V.G. Evolution of Cognition: Towards the theory of origin of human logic // Foundations of Science. 2000. Vol. 5. N.3. PP. 323-338.
  • Red'ko V.G. "Mathematical Modeling of Evolution" // Series on-line articles at Principia Cybernetica Project (PCP).
  • Red'ko V.G. Towards the evolutionary biocybernetics. // Proceedings of The Second International Symposium on Neuroinformatics and Neurocomputers, Rostov-on-Don, 1995. PP. 422-429.
  • Red'ko V.G. To the theory of evolution. The "life programs" origin model // Zhurnal obshchei biologii (Biology Bulletin Reviews). 1991. Vol.52. N.3. PP. 334-342 (In Russian).
  • Red'ko V.G. Adaptive syser // Biofizika. 1990. Vol. 35. N.6. PP. 1007-1011 (In Russian). The content of this paper is described in the PCP node "Adaptive syser".
  • Red'ko V.G. Spin glasses and evolution // Biofizika. 1990. Vol.35, N.5. PP. 831-834 (In Russian). The content of this paper is described in the PCP node "Spin-glass model of evolution".
  • Red'ko V.G. Behavior of sysers in coacervates // Biofizika (Biophysics). 1986. Vol. 31. N.4. PP. 701-703 (In Russian).
  • Red'ko V.G. Estimation of evolution rate in Eigen's and Kuhn's models // Biofizika (Biophysics). 1986. Vol. 31. N.3. PP. 511-516 (In Russian).

 

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