Development of S-modeling and digitalization

Vladimir D. Ilyin

Abstract


The review presents the relationship between the development of S-modeling (symbolic modeling of arbitrary objects in a human-machine environment) and digitalization (improvement of various types of activities based on information technology). In S-modeling, systems of symbols and corresponding systems of codes and signals, languages of S-modeling, methods of constructing, preserving, accumulating, searching and transmitting s-models of natural and inventive objects are studied [using computers, smartphones, and other programmable machines (called s-machines)]. The S-model of a natural or inventive object is considered as a mapping into a symbolic-code-signal environment, performed under constraints corresponding to the task for which the s-model is being built. S-modeling is used in science, engineering and other types of intellectual activity to build s-models of messages, interpret messages on s-models of concept systems, create network protocols and information resources, programming machine behavior, design, information interaction, training, etc. Computer programs, musical compositions, and other symbolic implementations of various designs can serve as examples of s-models.


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References


Ilyin, V.D. 2022. Symbolic Modeling (S-Modeling): an Introduction to Theory. In: Silhavy, R. (eds) “Artificial Intelligence Trends in Systems”. CSOC 2022. Lecture Notes in Networks and Systems. Springer, Cham. 502, 585–591. DOI: 10.1007/978-3-031-09076-9_54.

Kryuchkov, A.V. & Stepin, Yu.P. 2021. Kontseptual’nyye osnovy sistemy bez programmirovaniya i eye vozmozhnoye primeneniye dlya importozameshcheniya v protsessakh razrabotki spetsial’nogo programmnogo obespecheniya ASUP [The conceptual foundations of the system without programming and its possible application for import substitution in the development of special software ASUP]. Avtomatizatsiya, telemekhanizatsiya i svyaz’ v neftyanoy promyshlennosti [Automation, telemechanization and communication in the oil industry], 9(578), 60-68.

Gvozdeva, V.A. 2021. Intellektual’nyye tekhnologii v bespilotnykh sistemakh. Ser. Vyssheye obrazovaniye: Bakalavriat. Uchebnoye posobiye [Intelligent technologies in unmanned systems. Ser. Higher education: Bachelor's degree. Study guide]. Moscow: Nauchno-izdatel’skiy tsentr INFRA-M [INFRA-M Scientific Publishing Center], 176 p. ISBN: 978-5-16-016143-3.

Fedorov, A.A., Liberman, I.V. et al. 2021. Osnovy sozdaniya neyro-tsifrovykh ekosistem. Gibridnyy vychislitel’nyy intellekt [Fundamentals of creating neuro-digital ecosystems. Hybrid computational intelligence]. Kaliningrad: Baltiyskiy federal’nyy universitet im. Immanuila Kanta [Immanuel Kant Baltic Federal University], 241 p. ISBN: 978-5-9971-0636-2.

Zhirnov, V.V., Solonskaya, S.V. 2021. Metod preobrazovaniya simvol’nykh radarnykh otmetok malozametnykh podvizhnykh ob”yektov na osnove effekta Tal’bota [The method for converting symbolic radar markings of inconspicuous moving objects based on the Talbot effect]. Radіotekhnіka: Vseukraїns’kiy mіzhvіdomchiy naukovo-tekhnіchniy zbіrnik [Radio engineering: All-Ukrainian interdepartmental scientific and technical collection], 2(205), 129–137. DOI: 10.30837/rt.2021.2.205.14.

Dorenskaya, E.A., Kulikovskaya, A.A., Semënov, Yu.A. 2020. Yazyk opisaniya problemy i issledovaniye ego vozmozhnostey [The language of the problem description and the study of its possibilities]. Sovremennyye informatsionnyye tekhnologii i IT-obrazovaniye [Modern information technologies and IT education], 16(3), 653-663.

Weinstein, Yu.V., Shershneva, V.A. 2020. Adaptivnoye elektronnoye obucheniye v sovremennom obrazovanii [Adaptive e-learning in modern education]. Pedagogika [Pedagogy], 5, 48-57.

Shvalov, D.V., Kravchenko, V.A., Shirapov, D.Sh. 2019. Automated Logic-Mathematical Modeling of Railway Automation Devices Technical Condition. 2019 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon), 1-4 Oct. 2019, Vladivostok, Russia. Publisher: IEEE. DOI: 10.1109/FarEastCon.2019.8934943.

Bauer, V.P., Eremin, V.V., Sil’vestrov, S.N., Smirnov, V.V. 2019. Ekonomicheskoye modelirovaniye protsessov tsifrovoy transformatsii [Economic modeling of digital transformation processes]. Zhurnal ekonomicheskoy teorii [Journal of Economic Theory], 16(3), 428-443.

Kravchenko, V.A., Shirapov, D.Sh. 2018. Logic-Functional Modeling of Nonlinear Radio Engineering Systems. 2018 International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon), 3-4 Oct. 2018, Vladivostok, Russia. Publisher: IEEE. DOI:10.1109/FarEastCon.2018.8602769.

Ilyin, V.D. 1989. Sistema porozhdeniya programm [Program generating system]. Moscow: Nauka. 264 p. ISBN: 5-02-006578-1.

Ilyin, V.D., Sokolov, I.A. 2007. Simvol’naya model’ sistemy znaniy informatiki v cheloveko-avtomatnoy srede [The symbolic model of the informatics knowledge system in a human-automaton environment]. Informatika i eye primeneniya [Informatics and Applications], 1(1), 66-78.

Newell, A., Simon, H. 1976. Computer science as empirical inquiry: symbols and search. Commun. ACM, 19(3), 113–126. DOI: 10.1145/360018.360022.

Kay, A. 1975. Personal Computing. Palo Alto, California, USA: Learning Research Group. Xerox Palo Alto Research Center. Available at: http://worrydream.com/refs/Kay%20-%20Personal%20Computing.pdf (accessed November 14, 2022).

Ilyin, A.V., Ilyin, V.D. 2021. Updated methodology for task knowledge based development of parallel programs. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds.) CoMeSySo 2021. LNNS, 231, 319–328. Springer, Cham. DOI: 10.1007/978-3-030-90321-3_25.


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