EFFICIENCY OF THE COLLECTIVE MISSION BY A MULTIGENT HETEROGENEOUS GROUP
Abstract
The article deals with study оf the criteria, parameters and performance indicators for the implementation of the collective mission of extended space monitoring by a group that includes control objects with different functionality. The most urgent military-technical task of recent times – monitoring of extended spaces- is considered as an example of a mission. A feature of the article is the assumption about of hazardous zones in the monitoring area. Any counteraction from potentially critical objects may significantly limit the capabilities and even disable the monitoring tools. This proviso affects for implementation of the mission by the group and leads to a revision of the group collective strategies and individual strategies for monitoring tools, their movement routes, and decision-making algorithms and etc. Monitoring tools are modeled as intelligent agents trained by the "collectivism" paradigm. It provides a common resource of situational awareness of the group, the organization of negotiations between agents and mutual assistance to each other in the event of problem situations. A general approach has been developed to evaluate the effectiveness of solving collective problems by a heterogeneous group of agents, taking into account the objective function, resource intensity of the entire mission and organizing active interaction between agents. It is proposed that the mission efficiency characteristic expressed as a weighted sum of the normalized indicators of the parameters of the agents' functions with the weights "significance of the function for the mission" and "value of the object". It is shown that the loss of efficiency in the performance of a collective mission in the event of problematic situations with an agent (active enemy action, breakdown, lack of the necessary functionality, resources, etc.) can be compensated by the required functionality of other agents of the group with the appropriate reconfiguration of tasks.
References
of application], ed. by V.I. Syryamkina. Tomsk: STT, 2018, 140 p.
2. Abrosimov V., Mochalkin А. Collective behavior strategy development based on friendship of
robots, Proceedings of 4th International Conference on Mechatronics and Robotics Engineering
(ICMRE), Valenciennes, France, pp. 38-4. DOI: https://doi.org/10.1145/3191477.3191479.
3. Rzevski G., Skobelev P. Managing Complexity. Wit Pr/Computational Mechanics, 2014, 216 p.
4. Mayorov I.V. Mul'tiagentnye modeli i tekhnologii situatsionnogo upravleniya resursami
predpriyatiy v usloviyakh neopredelennosti: dis. ... kand. tekhn. nauk [Multi-agent models and
technologies of situational management of enterprise resources in conditions of uncertainty:
cand. of eng. sc. diss.]: 05.13.01. Samara: FGBOU VO Samarskiy gosudarstvennyy
tekhnicheskiy universitet, 2017, 259 p.
5. Kolesnikov A.V. Metodika kolichestvennoy otsenki missii organizatsii [Methodology of quantitative
assessment of the organization's mission], Vestnik REU im. G.V. Plekhanova [Bulletin
of Plekhanov Russian University of Economics], 2017, No. 5 (95), pp. 119-125.
6. Korotkov E.M. Menedzhment: uchebnik dlya bakalavrov [Management: textbook for bachelors].
3rd ed. Moscow: ID Yurayt, 2014, 684 p.
7. Sidorenkov A.V., Ul'yanova N.Yu. Upravlenie effektivnost'yu grupp i komand v organizatsii:
ucheb. posobie [Managing the effectiveness of groups and teams in an organization: a textbook].
Rostov-on-Donu: Izd-vo YuFU, 2016, 328 p.
8. Karpov V.E. Kollektivnoe povedenie robotov. ZHelaemoe i deystvitel'noe [Collective behavior
of robots. Wishful and valid], Sovremennaya mekhatronika: Sb. nauchnykh trudov
Vserossiyskoy nauchnoy shkoly (g. Orekhovo-Zuevo, 22-23 sentyabrya 2011) [Modern mechatronics:
Collection of scientific papers of the All-Russian Scientific School (Orekhovo-
Zuyevo, September 22-23, 2011)]. Orekhovo-Zuevo, 2011, pp. 35-51. Available at:
https://publications.hse.ru/chapters/51216080 (accessed 02 November 2022).
9. Pavlov A.S. Metodika planirovaniya traektorii dvizheniya gruppy mobil'nykh robotov v
neizvestnoy zamknutoy srede s prepyatstviyami [Methodology for planning the trajectory of a
group of mobile robots in an unknown closed environment with obstacles], Sistemy upravleniya,
svyazi i bezopasnosti [Control, communication and security systems], 2021, No. 3, pp. 38-59.
10. Melnik Е., Safronenkova I, Kapustyan S. The Efficiency Improvement of Robots Group Operation
by Means of Workload Relocation, Procedings of the International Conference on Interactive
Collaborative Robotics, 2021, pp. 126-137. DOI: 10.1007/978-3-030-87725-5.
11. Taeyong C., Jongwoo P., Jeong-Jung K., Young-Sik S., Hyunuk S. Work Efficiency Analysis
of Multiple Heterogeneous Robots for Harvesting Crops in Smart Greenhouses, Agronomy,
2022, No. 12 (11):2844. DOI: 10.3390/agronomy12112844.
12. Bakirov A.K., Kiril'chenko A.A. Problemy upravleniya raspredelennymi mobil'nymi sistemami
[Problems of management of distributed mobile systems]. Moscow, 2000, 23 p.
13. Essers M.S., Vaneker T.N.J. Developing Concepts for Improved Efficiency of Robot Work Preparation,
Procedings CIRP, 2013, Vol. 7, pp. 515-520. DOI.org/10.1016/j.procir.2013.06.025.
14. Вeloglazov D., Pereverzev V., Soloviev V., Pshikhopov V., Morozov R. Method of Formation of
Quantitative Indicators of Complexity of the Environment by a Group of Autonomous Mobile
Robots, Journal of Robotics, 2020, No. 3, pp. 1-14 DOI:10.1155/2020/6874291.
15. Altshuler Н., Wagner I.V., Bruckstein F.M. With caution-decreasing a swarm robotics' efficiency
by imprudently enhancing the robots' capabilities, IEEE Xplore Conference: Autonomous
Robots and Agents, 2009. DOI: 10.1109/ICARA.2000.4804014.
16. Elshamy W. Adaptive Control in Swarm Robotics Computer Science, 2021. Available at:
https://www.semanticscholar.org/paper/Adaptive-Control-in-Swarm-Robotics-Elshamy/
b112317012d4380a0311276936ddefd7c8cddd16.
17. Hayes А.T. How Many Robots? Group Size and Efficiency in Collective Search Tasks, Distributed
Autonomous Robotic Systems, 2002, No. 5, pp. 289-298. DOI: 10.1007/978-4-431-65941-9_29.
18. Mochalkin A.S., Voshchuk D.S., Voshchuk G.Yu., Mayorov I.V. Razrabotka setetsentricheskoy
intellektual'noy sistemy adaptivnogo planirovaniya deystviy gruppy avtonomnykh
bespilotnykh apparatov dlya soglasovannogo vypolneniya postavlennykh zadach [Development
of a network-centric intelligent system for adaptive planning of actions of a group of autonomous
unmanned vehicles for the coordinated performance of assigned tasks], Upravlenie i
obrabotka informatsii v tekhnicheskikh sistemakh: Tez. dokl. X Vserossiyskoy nauch.-prakt.
konf. Perspektivnye sistemy i zadachi upravleniya [Management and processing of information
in technical systems: Abstracts of the X All-Russian Scientific and Practical Conference Perspective
systems and management tasks.]. Rostov-on-Don, 2015, pp. 166-172.
19. Mayorova V.I., Bannikov A.M., Grishko D.A., Zharinov I.S., Leonov V.V., A.G. Toporkov, Kharlan
A.A. Kontrol' sostoyaniya sel'skokhozyaystvennykh poley na osnove prognozirovaniya dinamiki
indeksa NDVI po dannym kosmicheskoy mul'tispektral'noy i giperspektral'noy s"emki [Monitoring
the state of agricultural fields based on forecasting the dynamics of the NDVI index according to the
data of space multispectral and hyperspectral surveys], Nauka i obrazovanie [Science and Education],
2013, No. 7, pp. 199-228.
20. Skobelev P. Multi-Agent Systems for Real Time Adaptive Resource Management, Industrial
Agents: Emerging Applications of Software Agents in Industry, Eds.: P. Leitão, S. Karnouskos.
Elsevier, 2015, pp. 207-230.
