Russian version English version
Volume 5   Issue 2   Year 2010
Red’ko V.G.

Modeling of Cognitive Evolution as a Perspective Direction of Investigations on the Border of Biology and Mathematics

Mathematical Biology & Bioinformatics. 2010;5(2):215-229.

doi: 10.17537/2010.5.215.

References

 

  1. Kritika chistogo razuma (Kritik der reinen Vernunft). Moscow; 1964. Vol. 3. P. 69-695 (in Russ.).
  2. Kant I. Prolegomeny ko vsiakoi budushchei metafizike, mogushchei poiavit'sia kak nauka (Prolegomena zu einer jeder künftigen Metaphysik, die als Wissenschaft wird auftreten können). Moscow; 1965. Vol. 4. P. 67-210 (in Russ.).
  3. Lorenz K. In: Evoliutsiia. Iazyk. Poznanie (Learning, Development and Culture: Essays in Evolutionary Epistemology). Ed. Merkulov I.P. Moscow; 2000. P. 15-41.
  4. Matematicheskaia teoriia logicheskogo vyvoda (Mathematical Theory of Logical Induction). Ì.: Nauka; 1967 (in Russ.).
  5. Turchin VF. A constructive interpretation of the full set theory. Journal of Symbolic Logic. 1987;52(1):172-201. doi: 10.2307/2273872
  6. Turchin VF. The Phenomenon of Science: A Cybernetic Approach to Human Evolution. Columbia Univ. Pr.; 1977. 348 p.
  7. From Animals to Animats. Proceedings of the First International Conference on Simulation of Adaptive Behavior. Eds. Meyer J.-A., Wilson S.W. Cambridge: MIT Press; 1991.
  8. Ot modelei povedeniia k iskusstvennomu intellektu (From Behavoir to Artificial Intelligence). Ed. Redko VG. 2006. (in Russ.)
  9. Nepomnyashchikh VA. Novosti iskusstvennogo intellekta (Artificial Intelligence News). 2002;2:48-53 (in Russ.).
  10. Donnart JY, Meyer JA. Learning reactive and planning rules in a motivationally autonomous animat. IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics. 1996;26(3):381-395.
  11. Gaaze-Rapoport MG, Pospelov DA. Ot ameby do robota: modeli povedeniia (From Ameba to Robot: Patterns of Behavior). Moscow; 2004.
  12. Khaikin S. Neural networks: complete course. Ì.: Publishing house “Williams”; 2008. 1104 p.
  13. Holland JH. Adaptation in Natural and Artificial Systems. 1st edn. Ann Arbor, MI: The University of Michigan Press; 1975. 2nd edn. Boston, MA: MIT Press; 1992.
  14. Holland JH, Holyoak KJ, Nisbett RE, Thagard P. Induction: Processes of Inference, Learning, and Discovery. Cambridge: MIT Press; 1986.
  15. Sutton R, Barto A. Reinforcement Learning: An Introduction. Cambridge: MIT Press; 1998. doi: 10.1016/S1474-6670(17)38315-5
  16. Vaintsvaig MN, Poliakova MP. O modelirovanii myshleniia. In: Ot modelei povedeniia k iskusstvennomu intellektu. Ed. Red'ko V.G. Moscow; 2006. P. 280-286 (in Russ.). doi: 10.1134/S0036029506040021
  17. In: From animals to animats 9: Proceedings of the Ninth International Conference on Simulation of Adaptive Behavior. Eds. Nolfi S, Baldassarre G, Calabretta R, Hallam J, Marocco D, Miglino O, Meyer J-A, Parisi D. LNAI. Berlin, Germany: Springer Verlag; 2006. P. 4095.
  18. Wilson SW. The animat path to AI. In: From Animals to Animats: Proceedings of the First International Conference on Simulation of Adaptive Behavior. Eds. Meyer J-A, Wilson SW. Cambridge: MIT Press; 1991. P. 15-21.
  19. Krichmar JL, Seth AK, Nitz DA, Fleischer JG, Edelman GM. Spatial navigation and causal analysis in a brain-based device modeling cortical-hippocampal interactions. Neuroinformatics. 2005;3(3):197-221. doi: 10.1385/NI:3:3:197
  20. Marocco D, Nolfi S. Origins of communication in evolving robots. In: From Animals to Animats 9: Proceedings of the Ninth International Conference on Simulation of Adaptive Behavior. Eds. Nolfi S, Baldassarre G, Calabretta R, Hallam J, Marocco D, Miglino O, Meyer J-A, Parisi D. LNAI. Berlin, Germany: Springer Verlag; 2006. V. 4095. P. 789-803. doi: 10.1007/11840541
  21. Nepomnyashchikh VA, Popov EE, Red’ko VG. A bionic model of adaptive searching behavior. Journal of Computer and Systems Sciences International. 2008;47(1):78-85. doi: 10.1134/S1064230708010103
  22. Gelfand IM, Tsetlin ML. DAN SSS (Proceedings of the Academy of Sciences of the USSR). 1961;137(2):295-298 (in Russ.).
  23. Nepomniashchikh VA, Red'ko VG. In: Dvenadtsataia natsional'naia konferentsiia po iskusstvennomu intellektu s mezhdunarodnym uchastiem KII-2010 (12th National Conference on Artificial Intelligence with International Participation (CAI-2010)). Moscow; 2010. V. 4. P. 122-127 (in Russ.).
  24. Red'ko V.G., Red'ko O.V. In: Nauchnaia sessiia NIIaU MIFI - 2010. KhII Vserossiiskaia nauchno-tekhnicheskaia konferentsiia "Neiroinformatika-2010" (9 Scientific Session of the Moscow Engineering Physics Institute (National Research Nuclear University) - 2010. XII All-Russian Scientific and Technical Conference "Neuroinformatics - 2010"): Publication in Conference Proceedings. Moscow; 2010. P. 191-198 (in Russ.).
  25. Red'ko V.G., Prokhorov D.V. In: Nauchnaia sessiia MIFI - 2004. VI Vserossiiskaia nauchno-tekhnicheskaia konferentsiia "Neiroinformatika-2004". (Scientific Session of the Moscow Engineering Physics Institute (National Research Nuclear University) - 2004. VI All-Russian Scientific and Technical Conference "Neuroinformatics - 2004"). Moscow; 2004. P. 77-84 (in Russ.).
  26. Baldwin JM. A new factor in evolution. American Naturalist. 1896;30:441-451. doi: 10.1086/276408
  27. Evolution, Learning, and Instinct: 100 Years of the Baldwin Effect. Eds. Turney P, Whitley D, Anderson R. Special Issue of Evolutionary Computation on the Baldwin Effect. 1996;4(3). doi: 10.1162/evco.1996.4.3.iv
  28. Grossberg S. Classical and instrumental learning by neural networks. Progress in Theoretical Biology. 1974;3:51-141. doi: 10.1016/B978-0-12-543103-3.50009-2
  29. Barto AG, Sutton RS. Simulation of anticipatory responses in classical conditioning by neuron-like adaptive element. Behav. Brain Res. 1982;4:221-235.
  30. Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior. Eds. Butz MV, Sigaud O, Pezzulo G, Baldassarre G. LNAI 4520, Berlin, Heidelberg: Springer Verlag; 2007.
  31. Witkowski M. An action-selection calculus. Adaptive Behavior. 2007;15(1):73-97. doi: 10.1177/1059712306076254
  32. Prescott TJ. Forced moves or good tricks in design space? Landmarks in the evolution of neural mechanisms for action selection. Adaptive Behavior. 2007;15(1):9-31. doi: 10.1177/1059712306076252
  33. Vityaev E. Knowledge Discovery. Computational cognition. Cognitive process modeling. Novosibirsk: Novosibirsk State University; 2006. 293 p. (in Russ.).
  34. Vityaev EE. Principals of Brain Activity, Supported by the Functional System Theory by P.K. Anokhin and Emotional Theory by P.V. Simonov. Neiroinformatika (Neuroinformatics). 2008;3(1):25-78 (in Russ.).
  35. Demin AV, Vityaev EE. Neiroinformatika (Neuroinformatics). 2008;3(1):79-108 (in Russ.).
  36. Red’ko VG, Beskhlebnova GA. Neirokomp'iutery: razrabotka, primenenie (Neurocomputers: Design and Applications). 2010;3:33-38 (in Russ.).
  37. Butz MV, Shirinov E, Reif K. Self-organizing sensorimotor maps plus internal motivations yield animal-like behavior. Adaptive Behavior. 2010;18(3-4):315-337. doi: 10.1177/1059712310376842
  38. Red’ko VG, Beskhlebnova GA. In: Integrirovannye modeli i miagkie vychisleniia v iskusstvennom intellekte (Integrated Models and Soft Computing in Artificial Intelligence): Proceedings of the V-th International Research and Practice Conference. Moscow; 2009. V. 1. P. 70-79 (in Russ.).
  39. Beskhlebnova GA, Red’ko VG. In: Chetvertaia mezhdunarodnaia konferentsiia po kognitivnoi nauke (Proceedings of 4-th International conference of cognitive science). 2010. Vol. 1. P. 174-175 (in Russ.).
Table of Contents Original Article
Math. Biol. Bioinf.
2010;5(2):215-229
doi: 10.17537/2010.5.215
published in Russian

Abstract (rus.)
Abstract (eng.)
Full text (rus., pdf)
References

 

  Copyright IMPB RAS © 2005-2024