Preview

Mekhatronika, Avtomatizatsiya, Upravlenie

Advanced search
Open Access Open Access  Restricted Access Subscription or Fee Access

Cognitive Tools for Abstract Thinking Autonomous Intelligent Mobile Systems

https://doi.org/10.17587/mau.24.317-326

Abstract

The actual problems of artificial intelligence related to the development of tools for abstract thinking of autonomous intelligent mobile systems are being solved, which allow planning purposeful behavior in hard-to-reach and aggressive environments for humans. Cognitive tools are proposed that provide intelligent systems with the ability to organize purposeful multi-stage activities related to solving complex problems, when a behavior plan is automatically built in some conditions of a problematic environment, and a given behavior goal is achieved in other operating conditions that are beyond the resolution of technical vision. An important feature of the proposed typical elements of knowledge representation and processing is that they allow intelligent systems to organize the output of solving complex problems, relying only on the data stored in the knowledge representation model and coming from the current operating conditions. In the general case, the developed knowledge model of intelligent systems for various purposes consists of declarative and procedural typical elements of their representation. For a formal description of typical elements of declarative knowledge representation, traditional semantic networks and various sets of restrictions are used, reflecting additional conditions for the future functioning of autonomous mobile intelligent systems. As for the formal description of the typical elements of the representation of procedural knowledge, regardless of a specific subject area, fuzzy semantic networks are used for this. This allows autonomous intelligent mobile systems to adapt to specific operating conditions in underdetermined problematic environments and perform complex tasks formulated by them on this basis. The practical significance of the results obtained lies in the effectiveness of their use for the development of intelligent problem solvers that provide autonomous intelligent mobile systems for various purposes with the ability to perform complex tasks in a priori underdetermined problematic environments by adapting the purposeful activity plan formed in general form to specific current operating conditions.

About the Authors

V. B. Melekhin
Dagestan State Technical University
Russian Federation

Makhachkala, 367015



M. V. Khachumov
Ailamazyan Program Systems Institute of Russian Academy of Sciences; Federal Research Center "Computer Science and Control"; Peoples’ Friendship University of Russia
Russian Federation

Veskovo, 152021

Moscow, 117313

Moscow, 117198



References

1. Kurpatov A. V. Thinking. System research, Moscow, Kapital, 2022, 672 p. (in Russian).

2. Gubajnovskij V. A. Artificial intelligence and the human brain, Moscow, Nauka, 2019, 254 p. (in Russian).

3. Melekhin V. B., Hachumov M. V. Planning the Behavior of Autonomous Intelligent Mobile Systems under Uncertainty, St. Petersburg, Politekhnika, 2022, 276 p. (in Russian).

4. Melekhin V. B., Hachumov M. V. Instrumental means of controlling the expedient behavior of self-organizing autonomous intelligent agents, Mekhatronika, avtomatizaciya, upravlenie, 2021, vol. 22, no. 4, pp. 171— 80 (in Russian).

5. Karpov V. E., Karpova I. P., Kulinich A. A. Social communities of robots, Moscow, LENAND, 2019, 352 p. (in Russian).

6. Melekhin V. B., Khachumov M. V. Principle of Constructing Procedures for Planning Behavior of Autonomous Intelligent Robots Based on Polyvariable Conditionally Dependent Predicates, Automation and remote control, 2022, vol. 83, no. 4, pp. 593—605.

7. Gaze-Rapoport M. G., Pospelov D. A. From amoeba to robot. Behavior models, Moscow, URSS, 2019, 304 p. (in Russian).

8. Kelly A. Mobile Robotics: Mathematics, Models, and Methods, Cambridge, Cambridge University Press, 2013, 808 p.

9. Melekhin V. B., Khachumov M. V. Planning polyphasic behavior of autonomous intelligent mobile systems in uncertain environments, Information and Control Systems, 2021, no. 4 (113), pp. 28—36 (in Russian).

10. Melekhin V. B., Khachumov M. V. The principle of object recognition in a problematic environment in the process of planning the behavior of an autonomous intelligent mobile system, Morskie intellektual’nye tekhnologii, 2022, no. 1—3 (55), pp. 181—187 (in Russian).

11. Gonzalez R. C., Woods R. E. Digital image processing, London, Pearson, 2018, 1168 p.

12. Russell S., Norvig P. Artificial Intelligence: A Modern Approach, Pearson, 2020, 1216 p.

13. Ostrouh A. V. Intelligent systems, Krasnoyarsk, Nauchnoinnovacionnyj centr, 2020, 316 p. (in Russian).

14. Melekhin V. B., Hachumov V. M. Elements of conceptual thinking in planning the behavior of autonomous intelligent agents, Mekhatronika, avtomatizaciya, upravlenie, 2021, vol. 22, no 8, pp. 411—419 (in Russian).

15. Melekhin V. B., Hachumov V. M. Fuzzy semantic networks as an adaptive model of knowledge representation of autonomous intelligent systems, Scientific and Technical Information Processing, 2021, vol. 48, no 5, pр. 333—341.

16. Filimonov A. B., Filimonov N. B. Situational approach in tasks of automated control of technical objects, Mekhatronika, avtomatizaciya, upravlenie, 2018, vol. 19, no. 9, pp. 562—578 (in Russian).

17. Zaden L. A. The concept of a linguistic variable and its application to approximate reasoning, Part I: Information Sciences, 1975, vol. 8, pp. 199—249; Part II: Information Sciences, 1975, vol. 8, pp. 301—357; Part III: Information Sciences, 1975, vol. 9, pp. 43—80.

18. Flegontov A. V., Vilkov V. B., CHernyh A. K. Modeling of decision making problems with fuzzy initial data, Moscow, Lan’, 2020, 332 p. (in Russian).


Review

For citations:


Melekhin V.B., Khachumov M.V. Cognitive Tools for Abstract Thinking Autonomous Intelligent Mobile Systems. Mekhatronika, Avtomatizatsiya, Upravlenie. 2023;24(6):317-326. (In Russ.) https://doi.org/10.17587/mau.24.317-326

Views: 290


ISSN 1684-6427 (Print)
ISSN 2619-1253 (Online)