Expert Systems with Cognitive Models Elements as an Alternative Path for the Development of Artificial Intelligence:Philosophical and Methodological Aspects

A comparison of the concepts of artificial intelligence and expert systems is presented with regard to their application in decision-making processes. The paper substantiates the proposition that the development and advancement of expert systems incorporating elements of cognitive models may serve as an alternative approach to the development of artificial intelligence. Philosophical and methodological aspects of the emergence and evolution of expertise and expert communities are identified and analyzed. Cognitive modeling, based on the study and understanding of human intelligence and perception, is proposed as an approach for developing computer models capable of reproducing cognitive processes. It is shown that, from a philosophical perspective, the development of expert systems with elements of cognitive models represents a transition from a mechanistic understanding of artificial intelligence to a deeper and more comprehensive approach that takes into account the complexity and multidimensional nature of human thought. Such systems make it possible to model complex cognitive processes more accurately, provide greater flexibility in solving a wide range of tasks, and constitute a promising direction for the development of intelligent decision-support systems.

EDN QBIWSM   

References
[1] Yun H., Neusypin K.A., Selezneva M.S., Tsibizova T.Yu. Metodologiya upravleniya innovatsionnym razvitiem slozhnykh sotsialno-ekonomicheskikh sistem v usloviyakh informatsionnogo obschestva [Methodology for managing the innovative development of complex socio-economic systems in the information society]. In: Tsifrovye tekhnologii v inzhenernom obrazovanii: novye trendy i opyt vnedreniya. Sbornik trudov Mezhdunarodnogo foruma (Moscow, November 28–29, 2019) [Digital technologies in engineering education: new trends and implementation experience. Proceedings of the international forum (Moscow, November 28–29, 2019)]. Moscow, Bauman Press, 2020, pp. 440–444.
[2] Galandarova Sh., Myademinova G., Arnepesov D., Orunova A. Revolyutsiya v mire dannykh: iskusstvennyy intellekt i obrabotka bol’shikh dannykh kak dvigatel sovremennykh komp’yuternykh tekhnologiy [Revolution in the world of data: artificial intelligence and big data processing as a driver of modern computer technologies]. Ceteris Paribus, 2023, no. 12, pp. 19–21.
[3] Yampolskiy R.V. AI: Unexplainable, unpredictable, uncontrollable. New York, Chapman and Hall/CRC, 2024 [In Russ.: Yampolskiy R.V. II: Neob"yasnimyy, nepredskazuemyy, nekontroliruemyy. Moscow, NOVA Creative Group, 2025, 360 p.].
[4] Petrovsky V.D. Primenenie iskusstvennogo intellekta i mashinnogo obucheniya v sistemakh podderzhki prinyatiya resheniy [Application of artificial intelligence and machine learning in decision support systems]. In: Nauka segodnya: aktual’nye issledovaniya. Materialy mezhdunarodnoy nauchno-prakticheskoy konferentsii (Moscow, June 11, 2025) [Science today: current research. Proceedings of the international scientific and practical conference (Moscow, June 11, 2025)]. Saratov, Akademiya Biznesa, 2025, pp. 23–28.
[5] Shkabura A.D., Parfenchik Z.A., Mashlyakevich M.S. Ekspertnye sistemy kak prikladnaya oblast’ iskusstvennogo intellekta [Expert systems as an applied field of artificial intelligence]. In: Tekhnologii sovremennogo obrazovaniya. Materialy mezhdunarodnoy konferentsii (Minsk, October 24–25, 2024) [Technologies of modern education. Proceedings of the international conference (Minsk, October 24–25, 2024)]. Minsk, BNTU Publ., 2025, pp. 141–145.
[6] Volosatova A.A. et al. Rol i znachenie ekspertnykh soobschestv v protsesse prinyatiya upravlencheskikh resheniy: sravnitelnyy analiz natsionalnogo i mezhdunarodnogo opyta [The role and importance of expert communities in management decision-making: a comparative analysis of national and international experience]. Vestnik evraziyskoy nauki — The Eurasian Scientific Journal, 2020, vol. 12, no. 5, p. 13.
[7] Mikhaleva O.A. Matematicheskoe i programmnoe obespechenie obrabotki rezultatov gruppovogo otsenivaniya dlya upravleniya setevoy ekspertizoy v raspredelennoy srede: Dis. … Cand. tech. nauk [Mathematical and software support for processing group evaluation results for managing network expertise in a distributed environment]. Bryansk, 2020, 153 p.
[8] Gubanov D.A., Korgin N.A., Novikov D.A., Raykov A.N. Setevaya ekspertiza [Network expertise]. Moscow, Egves Publ., 2011, 169 p.
[9] Giarratano J., Riley G. Expert systems: principles and programming. Boston, PWS Publishing, 1994 [In Russ.: Giarratano J., Riley G. Ekspertnye sistemy: printsipy razrabotki i programmirovanie. Moscow, I.D. Williams Publ., 2007, 1152 p.].
[10] Kholodnaya M.A. Intellekt [Intelligence]. Bolshaya rossiyskaya entsiklopediya: nauchno-obrazovatelnyy portal [Great Russian encyclopedia: scientific and educational portal]. Available at: https://bigenc.ru/c/intellekt-47cb87/?v=3383263 (accessed April 29, 2026).
[11] Alterman A.D., Parfenova A.S., Lushnikov N.D., Klochek M.S. Ekspertnye sistemy kak vektor razvitiya iskusstvennogo intellekta [Expert systems as a vector of artificial intelligence development]. In: Vnedrenie rezultatov innovatsionnykh razrabotok: problemy i perspektivy. Sbornik statey mezhdunarodnoy nauchno-prakticheskoy konferentsii (Magnitogorsk, January 9, 2020). Part 1 [Implementation of innovative development results: problems and prospects. Proceedings of the International scientific and practical conference (Magnitogorsk, January 9, 2020). Part 1]. Magnitogorsk, Omega Science, 2020, pp. 76–78.
[12] Usmonzoda F.B., Samad M.Z. Evolyutsiya iskusstvennogo intellekta i ekspertnye sistemy [The evolution of artificial intelligence and expert systems]. Internauka, 2025, no. 25-1, pp. 17–19.
[13] Tsibizova T.Yu., Panilov P.A. Kognitivnoe modelirovanie i sistemnyy analiz vysokointellektualnykh sistem [Cognitive modeling and systems analysis of highly intelligent systems]. Moscow, Bauman Press, 2025, 116 p.
[14] Miroshnichenko D.V. Rasshirenie vozmozhnostey iskusstvennogo intellekta s pomoschyu ekspertnykh sistem [Expanding the capabilities of artificial intelligence through expert systems]. Nauchnyy aspekt, 2024, vol. 4, no. 5, pp. 383–387.
[15] Gulyaeva A.V., Gulyaev D.A. Integratsiya ekspertnykh sistem i iskusstvennogo intellekta: arkhitektura, algoritmy i perspektivy [Integration of expert systems and artificial intelligence: architecture, algorithms, and prospects]. In: Tsifrovaya transformatsiya: nauka, tekhnologii, innovatsii: sbornik statey mezhdunarodnoy nauchno-prakticheskoy konferentsii (Kazan, February 1, 2025) [Digital transformation: science, technology, innovations: proceedings of the international scientific and practical conference (Kazan, February 1, 2025)]. Ufa, Aeterna Publ., 2025, pp. 35–37.
[16] Vlasova A.S., Podlesnyy A.O. Kognitivnye modeli v informatsionnykh sistemakh [Cognitive models in information systems]. Intellektualnyy potentsial XXI veka: stupeni poznaniya. Novosibirsk, Tsentr razvitiya nauchnogo sotrudnichestva, 2013, no. 19, pp. 88–91.
[17] Panilov P.A., Tsibizova T.Yu. Kognitivnoe modelirovanie: evolyutsiya metodov i ikh vliyanie na ponimanie chelovecheskogo intellekta [Cognitive modeling: evolution of methods and their influence on understanding human intelligence]. In: Russkiy inzhener. Sbornik tezisov II Vserossiyskogo kongressa s mezhdunarodnym uchastiem (Moscow, October 30 – November 1, 2024) [Russian engineer. Proceedings of the II All-Russian congress with international participation (Moscow, October 30 – November 1, 2024)]. Moscow, Bauman Press, 2024, pp. 306–308.
[18] Panilov P.A., Tsibizova T.Yu., Komardin M.A. Kognitivnoe modelirovanie i teoriya sistem: novye podkhody k opisaniyu adaptivnosti i samoorganizatsii [Cognitive modeling and systems theory: new approaches to describing adaptability and self-organization]. In: Russkiy inzhener. Sbornik tezisov III Vserossiyskogo kongressa s mezhdunarodnym uchastiem (Moscow, October 29–31, 2025) [Russian engineer. Proceedings of the III All-Russian congress with international participation (Moscow, October 29–31, 2025)]. Moscow, Bauman Press, 2025, pp. 246–248.
[19] Panilov P.A. Kognitivnye refreymingi v predvidenii i predotvraschenii multipleksnykh ugroz kriticheskoy infrastrukture [Cognitive reframing in the forecasting and prevention of multiplex threats to critical infrastructure]. Virtualnaya kommunikatsiya i sotsialnye seti, 2024, vol. 3, no. 4, pp. 316–325.
[20] Panilov P.A., Tsibizova T.Yu. Emergentnye tendentsii v kognitivnom modelirovanii: integratsiya gibridnykh arkhitektur, adaptivnykh strategiy i multiagentnykh sistem [Emergent trends in cognitive modeling: integration of hybrid architectures, adaptive strategies and multi-agent systems]. In: Russkiy inzhener. Sbornik tezisov III Vserossiyskogo kongressa s mezhdunarodnym uchastiem (Moscow, October 29–31, 2025) [Russian engineer. Proceedings of the III All-Russian congress with international participation (Moscow, October 29–31, 2025)]. Moscow, Bauman Press, 2025, pp. 249–251.