Classification and conditions of application of algorithms for automatic ontologization of the state space of a general artificial intelligence agent under the control of neurocognitive architecture
Z.V. Nagoev, I.A. Pshenokova, M.I. Anchekov, K.Ch. Bzhikhatlov,
B.A. Atalikov, S.A. Kankulov, A.Z. Enes
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Abstract. The purpose of the study is to form an algorithmic base for ontologizing the state space of a general artificial intelligence agent. The main objectives of the work are the classification of algorithms for the autonomous synthesis of ontologies of the “agent-environment” system and the selection of conditions for their application. The form and contents of the main ontologization algorithms for the state space of an intelligent agent of artificial general intelligence are determined and their classification is constructed. The mechanisms for the formation of concepts of functional representation of entities in the state space of an intelligent agent based on dynamic generation “on demand” are substantiated. A meta-algorithm for selecting private ontologization algorithms has been constructed depending on the selected application conditions.
Keywords: automatic construction of ontologies, artificial general intelligence, multi-agent systems, neurocognitive architectures
For citation. Nagoev Z.V., Pshenokova I.A., Anchekov M.I. et al. Classification and conditions of application of algorithms for automatic ontologization of the state space of a general artificial intelligence agent under the control of neurocognitive architecture. News of the Kabardino-Balkarian Scientific Center of RAS. 2023. No. 6(116). Pp. 210–225. DOI: 10.35330/1991-6639-2023-6-116-210-225
References
- Russell S., Norvig P. Artificial Intelligence: A Modern Approach (AIMA). 2nd ed. Moscow: Williams, 2007. 1424 p.
- Nagoev Z.V. Intellektika, ili Myshleniye v zhivykh i iskusstvennykh sistemakh [Intelligence, or Thinking in living and artificial systems]. Nalchik: Izdatel’stvo KBNTS RAN, 2013. 232 p. (In Russian)
- Nagoev Z., Nagoeva O., Anchekov M. et al. The symbol grounding problem in the system of general artificial intelligence based on multi-agent neurocognitive architecture. Cognitive Systems Researchthis link is disabled, 2023. No. 79. Pp. 71–84.
- Nagoev Z.V., Nagoeva O.V. Obosnovaniye simvolov i mul’tiagentnyye neyrokognitivnyye modeli semantiki yestestvennogo yazyka [Symbol grounding and multi-agent neurocognitive models of natural language semantics]. Nalchik: Izdatel’stvo KBNTS RAN, 2022. 150 p. (In Russian)
- Apshev A.Z., Atalikov B.A., Kankulov S.A. et al. Ontophylogenetic algorithms for the synthesis of phenotypes of intelligent software agents for use in multi-generation optimization problems of control neurocognitive architectures. News of the Kabardino-Balkarian Scientific Center of RAS. 2022. No. 6(110). Pp. 76–91. DOI: 10.35330/1991-6639-2022-6-110-76-91. (In Russian)
- Nagoev Z.V. Ontoneuromorphogenetic modeling. News of the Kabardino-Balkarian Scientific Center of RAS. 2013. No. 4(54). Pp. 46–56. (In Russian)
- DiFilippo N.M., Jouaneh M.K. Using the soar cognitive architecture to remove screws from different laptop models. IEEE Trans Autom Sci Eng. 2018. No. 16(2). Pp.767–780.
- Fittner M., Brandstatter C. How human inspired learning enhances the behavior of autonomous agents. JCP. 2018. No 13(2). Pp. 154–160.
- Gobet F., Lane P. The chrest architecture of cognition: The role of perception in general intelligence. In: 3d Conference on Artificial General Intelligence (AGI-2010), Atlantis Press. https://doi.org/10.2991/agi.2010.20
- González-Casillas A., Parra L., Martin L. et al. Towards a model of visual recognition based on neurosciences. Proc Comput Sci. 2018. Vol. 145. Pp. 214–231.
Information about the authors
Nagoev Zalimkhan Vyacheslavovich, Candidate of Technical Sciences, General Director of the Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
zaliman@mail.ru, ORCID: https://orcid.org/0000-0001-9549-1823
Pshenokova Inna Auesovna, Candidate of Physical and Mathematical Sciences, Head of the Laboratory “Intelligent Living Environments”, Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
pshenokova_inna@mail.ru, ORCID: https://orcid.org/0000-0003-3394-7682
Anchekov Murat Inusovich, Researcher of the Laboratory “Molecular Selection and Biotechnology”, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 224 Kirov street;
murat.antchok@gmail.com, ORCID: https://orcid.org/0000-0002-8977-797X
Bzhikhatlov Kantemir Chamalovich, Candidate of Physical and Mathematical Sciences, Head of the Laboratory “Neurocognitive Autonomous Intelligent Systems”, Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360002, Russia, Nalchik, 2 Balkarov street;
haosit13@mail.ru, ORCID: https://orcid.org/0000-0003-0924-0193
Atalikov Boris Anzorovich, Trainee Researcher of the Laboratory “Intellectual Habitats”, Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
atalikov10@gmail.com
Kankulov Sultan Akhmedovich, Trainee Researcher of the Laboratory “Intellectual Habitats”, Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
skankulov@mail.ru, ORCID: https://orcid.org/0000-0002-2996-7376
Enes Akhmed Zulfikar, Junior Researcher of the Laboratory “Computational Linguistics”, Institute of Computer Science and Problems of Regional Management – branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;
360000, Russia, Nalchik, 37-a I. Armand street;
ahmedenes@mail.ru, ORCID: https://orcid.org/0000-0003-3633-4910











