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Logical Probabilistic Biologically Inspired Cognitive Architecture

Part of the Lecture Notes in Computer Science book series (LNAI,volume 12177)


We consider a task-oriented approach to AGI, when any cognitive problem, perhaps superior to human ability, has sense given a criterion of its solution. In the frame of this approach, we consider the task of purposeful behavior in a complex probabilistic environment, where behavior is organized through self-learning. For that purpose, we suggest cognitive architecture that relies on the theory of functional systems. The architecture is based on the main notions of this theory: goal, result, anticipation of the result. The logical structure of this theory was analyzed and used for the control system of purposeful behavior development. This control system contains a hierarchy of functional systems that organizes purposeful behavior. The control system was used for modeling agents to solve the foraging task.


  • Architecture
  • Functional systems theory
  • Adaptive control system
  • Purposeful behavior
  • Goal-directed behavior

The first author financially supported by the Russian Foundation for Basic Research # 18-29-13027.

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  • DOI: 10.1007/978-3-030-52152-3_36
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  1. Anokhin, P.K.: Biology and Neurophysiology of the Conditioned Reflex and its Role in Adaptive Behavior. Pergamon Press, Oxford (1974)

    Google Scholar 

  2. Vityaev, E.E.: A formal model of neuron that provides consistent predictions. In: Chella, A., Pirrone, R., Sorbello, R., Johannsdottir, K.R. (eds.) Biologically Inspired Cognitive Architectures 2012. AISC, vol. 196, pp. 339–344. Springer, Heidelberg (2013).

    CrossRef  Google Scholar 

  3. Vityaev, E., Odintsov, S.: How to predict consistently? In: Cornejo, M.E., Kóczy, L.T., Medina, J., De Barros Ruano, A.E. (eds.) Trends in Mathematics and Computational Intelligence. SCI, vol. 796, pp. 35–41. Springer, Cham (2019).

    CrossRef  Google Scholar 

  4. Avi, P.: Practical Probabilistic Programming. Manning Publications, New York (2016)

    Google Scholar 

  5. Laird, J.E.: The Soar Cognitive Architecture. MIT Press, Cambridge (2012)

    CrossRef  Google Scholar 

  6. Sudakov, K.V.: The general theory of functional systems. Medicine, Moscow (1984). (in Russian)

    Google Scholar 

  7. Muhortov, V.V., Khlebnikov, S.V., Vityaev, E.E.: Improved algorithm of semantic probabilistic inference in task of 2-dimention animat. Neuroinformatics 6(1), 50–62 (2012). (in Russian)

    Google Scholar 

  8. Sutton, R., Barto, A.: Reinforcement Learning: An Introduction. MIT Press, Cambridge (1998)

    MATH  Google Scholar 

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Correspondence to Evgenii E. Vityaev .

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Vityaev, E.E., Demin, A.V., Kolonin, Y.A. (2020). Logical Probabilistic Biologically Inspired Cognitive Architecture. In: Goertzel, B., Panov, A., Potapov, A., Yampolskiy, R. (eds) Artificial General Intelligence. AGI 2020. Lecture Notes in Computer Science(), vol 12177. Springer, Cham.

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