Skip to main content
SpringerLink
Log in

Rapid Goal-Setting in Hierarchical Groups of Active Objects: I. Selected Group

  • ARTIFICIAL INTELLIGENCE
  • Published:
Journal of Computer and Systems Sciences International Aims and scope

Abstract

This article studies the problems of rapid goal-setting in hierarchical groups of active (anthropocentric) objects, by which the authors mean, primarily, groups of aircraft, united by the initial and situationally arising missions. A group of objects are assigned a mission before they start functioning. When a group performs the given mission in a deliberately or passively antagonistic environment, the following collision occurs: “Mission stage in progress: immediate threat to the mission.” This forces the group to solve the problem of rapid goal setting. A methodology for solving such problems is created, which entails conducting a system analysis of the subject area to identify the composition and interaction of the tactical-level onboard intelligent systems necessary to solve these problems; the presence of previously developed subject-independent images of the knowledge bases of the identified intelligent systems; and saturation of the knowledge bases of these systems with specific information (the mission being performed, the threat that has arisen, and specific information of the means of counteracting it available at the facilities). The resulting solution to the problem of rapid goal setting at unmanned facilities is immediately sent for implementation, and at facilities with a crew, the solution is implemented only with their consent. An illustrative example of solving a practically significant task of rapid goal-setting in aviation problems is given.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

Similar content being viewed by others

REFERENCES

  1. B. E. Fedunov, Tactical-Level Airborne Intelligent Systems for Anthropocentric Objects (Examples for Manned Aircraft) (De Libri, Moscow, 2018) [in Russian].

    Google Scholar 

  2. B. E. Fedunov, “Tactical-level onboard real-time advisory expert systems for manned aircraft as development and maintenance entities,” J. Comput. Syst. Sci. Int. 55 (4), 579–597 (2016).

    Article  Google Scholar 

  3. S. Yu. Zheltov and B. E. Fedunov, “Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: I. Structures of algorithms for the support of crew decision-making,” J. Comput. Syst. Sci. Int. 54 (3), 384–398 (2015).

    Article  Google Scholar 

  4. S. Yu. Zheltov and B. E. Fedunov, “Operational goal setting in anthropocentric objects from the viewpoint of the conceptual model called Etap: II. Operation modes of the on-board real-time advisory expert system and its dialog with the crew,” J. Comput. Syst. Sci. Int. 55 (3), 380–393 (2016).

    Article  Google Scholar 

  5. V. F. Gribkov and B. E. Fedunov, “The onboard information intelligent system “Situational awareness of the crew of combat aircraft,” in Intelligent Control Systems, Ed. by S. N. Vasil’ev (Mashinostroenie, Moscow, 2010), pp. 108–116 [in Russian].

    Google Scholar 

  6. B. E. Fedunov, “Electronic pilot: The point of no return will not be passed. Airborne operational advisory tactical-level expert systems for manned aircraft,” Aviapanorama, No. 1, 9–20 (2016).

  7. B. E. Fedunov, “Solution of problems according to precedent in knowledge bases of tactical onboard intelligent systems during the mission phases of a moving object,” J. Comput. Syst. Sci. Int. 62 (1), 1–10 (2023).

    Article  Google Scholar 

  8. B. E. Fedunov, N. D. Yunevich, and A. A. Plyatsovoi, RF Patent No. 2751377, October 29, 2020.

  9. B. E. Fedunov and N. D. Yunevich, “The real-time approach to solving the problems for the multicriterial choice of alternatives in the knowledge bases of onboard real-time advisory expert systems,” J. Comput. Syst. Sci. Int. 60 (3), 448–464 (2021).

    Article  Google Scholar 

  10. B. E. Fedunov, N. D. Yunevich, and A. A. Plyatsovoi, RF Patent No. 2724573, November 22, 2019.

  11. N. M. Grevtsov, S. N. Perchitz, B. E. Fedunov, and N. D. Yunevich, “Intellectual support of commander of escort jet fighter group in solving the task for the returning subgroup, which repulsed an attack of enemy jet fighters,” J. Comput. Syst. Sci. Int. 57 (4), 608–619 (2018).

    Article  Google Scholar 

  12. S. K. Galikhanov, B. E. Fedunov, and M. A. Shigina, “Construction of rendezvous trajectories in the knowledge bases of onboard operational-advisory expert systems of the flight stage,” J. Comput. Syst. Sci. Int. 61 (3), 395–406 (2022).

    Article  Google Scholar 

  13. G. Arkhangel’skii, Corporate Time Management: Encyclopedia of Solutions (Al’pinaBiznesBuks, Moscow, 2008) [in Russian].

  14. F. Yitzhak and L. H. Slowik, “Enriching goal-setting theory with time: An integrated approach,” Acad. Manage. Rev. 29 (3), 404–422 (2004).

    Article  Google Scholar 

  15. G. P. Latham, “The motivational benefits of goal-setting,” Acad. Manage. Exec. 18 (4), 126–129 (2004).

    Google Scholar 

  16. E. A. Locke and G. P. Latham, “Building a practically useful theory of goal setting and task motivation: A 35-year odyssey,” Am. Psychol. 57 (9), 705–717 (2002).

    Article  Google Scholar 

  17. D. E. Terpstra and E. J. Rozell, “The relationship of goal setting to organizational profitability,” Group Org. Manage. 19, 285–295 (1994).

    Article  Google Scholar 

  18. M. E. Buzikov, A. A. Galyaev, Yu. V. Guryev, K. B. Titov, E. I. Yakushenko, and S. N. Vassilyev, “Intelligent control of autonomous and anthropocentric on-board systems,” in XIII International Symposium “Intelligent Systems” (INTELS’18) (Procedia Computer Science, St. Petersburg, 2019), Vol. 150, pp. 10–18.

  19. M. Zabarankin, S. Uryasev, and R. Murphey, “Aircraft routing under the risk of detection,” Nav. Res. Logist. 53 (8), 728–747 (2006).

    Article  MathSciNet  Google Scholar 

  20. E. I. Yakushenko, Yu. V. Gur’ev, V. I. Eiduk, S. N. Vasil’ev, A. V. Dobrovidov, E. L. Kulida, E. P. Maslov, I. V. Tkachenko, A. M. Vishnevskii, and Yu. F. Shlemov, “Onboard control system for the secrecy of a marine underwater object with an operational advisory system,” Inf. Byull. Komp’yuternykh Inf. Tekhnol. 10, 9–16 (2012).

    Google Scholar 

  21. A. A. Galyaev and E. P. Maslov, “On the border patrolling problem,” J. Comput. Syst. Sci. Int. 50 (5), 837–846 (2011).

    Article  MathSciNet  Google Scholar 

  22. A. Lomuscio and J. Michaliszyn, “Verifying multi-agent systems by model checking three-valued abstractions,” in Proc. 14th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS'2015) (IFAAMAS, Istanbul–London, 2015), pp. 189–198.

Download references

Author information

Authors and Affiliations

  1. Moscow Aviation Institute (National Research University), 125080, Moscow, Russia

    S. K. Galikhanov & B. E. Fedunov

  2. State Research Institute of Aviation Systems (GosNIIAS), 125167, Moscow, Russia

    B. E. Fedunov & N. D. Yunevich

Authors
  1. S. K. Galikhanov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. E. Fedunov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. D. Yunevich
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to S. K. Galikhanov, B. E. Fedunov or N. D. Yunevich.

Additional information

Publisher’s Note.

Pleiades Publishing remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Galikhanov, S.K., Fedunov, B.E. & Yunevich, N.D. Rapid Goal-Setting in Hierarchical Groups of Active Objects: I. Selected Group. J. Comput. Syst. Sci. Int. 62, 492–507 (2023). https://doi.org/10.1134/S1064230723030048

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1064230723030048

Search

Navigation