Skip to main content
Log in

Selecting executor in a group of intellectual agents

  • Large Scale Systems Control
  • Published:
Automation and Remote Control Aims and scope Submit manuscript

Abstract

This paper suggests a formal lattice-based method to represent the desires and intentions of an intellectual agent and to select an executor in a group of such agents while planning a new task. The method is illustrated using an example of group control for unmanned aerial vehicles.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Abrosimov, V.K., Gruppovoe dvizhenie intellektual’nykh letatel’nykh apparatov v antagonisticheskoi srede (Group Motion of Smart Aircrafts in a Conflict Environment), Moscow: Nauka, 2013.

    Google Scholar 

  2. Birkhoff, G., Lattice Theory, Providence: AMS, 1967. Translated under the title Teoriya reshetok, Moscow: Nauka, 1984.

    MATH  Google Scholar 

  3. Gavrilova, T.A. and Khoroshevsky, V.F., Bazy znanii intellektual’nykh sistem (Knowledge Bases of Intelligent Systems), St. Petersburg: Piter, 2000.

    Google Scholar 

  4. Gorodetskii, V.I., A Survey on Teamwork of Autonomous Agents: Theories, Frameworks and Specification Languages (Part 1), Isk. Intell. Prinyat. Resh., 2011, no. 2, pp. 19–30.

    Google Scholar 

  5. Kalyaev, I.A., Gaiduk, A.R., and Kapustyan, S.G., Modeli i algoritmy kollektivnogo upravleniya v gruppakh robotov (Models and Algorithms of Collective Control in Groups of Robots), Moscow: Fizmatlit, 2009.

    MATH  Google Scholar 

  6. Kulinich, A.A., A Model of Agents (Robots) Command Behavior: The Cognitive Approach, Autom. Remote Control, 2016, vol. 77, no. 3, pp. 510–522.

    Article  MathSciNet  MATH  Google Scholar 

  7. Legovich, Yu.S. and Maksimov, D.Yu., LogicalModels for Choosing Solutions in Self-Organized Systems, Probl. Upravlen., 2013, no. 3, pp. 18–27.

    Google Scholar 

  8. Legovich, Yu.S. and Maksimov, D.Yu., Using Multivalued Logic for Decision Making in Self-Organizing Control Systems, Tr. V Mezhd. Konf. “Upravlenie razvitiem krupnomasshtabnykh sistem” (Proc. 5 Int. Conf. “Management of Large-Scale Systems Development” (MLSD’2011)), Moscow, 2011, pp. 130–135.

    Google Scholar 

  9. Legovich, Yu.S. and Maksimov, D.Yu., Dynamic Prioritization of Goals in Self-Organizing Control Systems, Tr. VI Mezhd. Konf. “Upravlenie razvitiem krupnomasshtabnykh sistem” (Proc. 6 Int. Conf. “Management of Large-Scale Systems Development” (MLSD’2012)), Moscow, 2012, pp. 285–288.

    Google Scholar 

  10. Maksimov, D.Yu., Decision Choice under Transformations in Control Systems, Tr. Mezhd. Konf. “Teoriya aktivnykh sistem” (Proc. Int. Conf. “Theory of Active Systems”), Burkov, V.N. and Novikov, D.A., Eds., Moscow, 2011, pp. 162–172.

    Google Scholar 

  11. Maksimov, D.Yu., Reconfiguring System Hierarchies with Multivalued Logic, Upravlench. Nauki Sovr. Rossii, 2014, vol. 2, no. 2, pp. 221–225.

    Google Scholar 

  12. Minin, A.A., Nazarova, A.V., and Ryzhova, T.P., Task Distribution in Decentralized Robotic System, Mekhantron. Avtomatiz. Kontr., 2014, no. 11, pp. 16–20.

    Google Scholar 

  13. Skobelev, P.O., Open Multi-agent Systems for Operational Information Processing in Decision Theory, Avtometriya, 2002, no. 6, pp. 45–61.

    Google Scholar 

  14. Rozhnov, A.V., Krivonozhko, V.E., and Lychev, A.V., Constructing Hybrid Intelligent Informational Environments and Components of Expert Systems with a Generalized Model of Analyzing the Operational Environment, Neirokomp. Razrabotka, Primen., 2013, no. 6, pp. 3–12.

    Google Scholar 

  15. Shvetsov, A.N., Agent-Oriented Systems: From Formal Models to Industrial Applications. www.ict.edu. ru/lib/index.php?id res=5656 (accessed February 3, 2015).

    Google Scholar 

  16. Yannikov, I.M., Fomin, P.M., Gabrichidze, T.G., and Zakharov, A.V., Application of Unmanned Aerial Vehicles for Exploration of Emergency Hard-to-Reach and Large-Scale Zones, Vektor Nauki TGU, 2012, no. 3(21), pp. 49–53.

    Google Scholar 

  17. Brooks, R.A., Intelligence without Representation, Artific. Intell., 1991, no. 47, pp. 139–159.

    Article  Google Scholar 

  18. Cohen, P. and Levesque, H.J., Teamwork, in Nous. Special Issue on Cognitive Science and Artifical Intelligence, 1991, no. 25(4), pp. 487–512.

    Google Scholar 

  19. Dias, M.B. and Stentz, A., A Free Market Architecture for Distributed Control of a Multirobot System, Proc. 6th Int. Conf. on Intelligent Autonomous Systems (IAS), Venice, Italy, July, 2000, pp. 115–122.

    Google Scholar 

  20. Grosz, B. and Kraus, S., Collaborative Plans for Complex Group Actions, Artific. Intell., 1996, no. 86, pp. 269–358.

    Article  MathSciNet  Google Scholar 

  21. Rao, A.S. and Georgeff, M.P., BDI Agents: From Theory to Practice, Proc. First Int. Conf. on Multi-Agent Systems, Lesser, V., Ed., AAAI Press/MIT Press, 1995, pp. 312–319.

    Google Scholar 

  22. Stentz, A. and Dias, M.B., A Free Market Architecture for Coordinating Multiple Robots, Tech. Report CMU-RI-TR-99-42, Robotics Institute, Carnegie Mellon University, December, 1999.

    Book  Google Scholar 

  23. Zlot, R., Stentz, A., Dias, M.B., and Thayer, S., Multi-Robot Exploration Controlled by a Market Economy, IEEE Int. Conf. on Robotics and Automation (ICRA), May 2002. http://frc.ri.cmu.edu/~xs/doc/icra02.pdf (accessed February 3, 2015).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yu. S. Legovich.

Additional information

Original Russian Text © Yu.S. Legovich, D.Yu. Maksimov, 2015, published in Upravlenie Bol’shimi Sistemami, 2015, No. 56, pp. 78–94.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Legovich, Y.S., Maksimov, D.Y. Selecting executor in a group of intellectual agents. Autom Remote Control 78, 1341–1349 (2017). https://doi.org/10.1134/S0005117917070153

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S0005117917070153

Navigation