Geodesic
Irrational behavioral strategies for a swarm of mini-robots
Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, Tome 17 (2021) no. 4, pp. 419-432
Cet article a éte moissonné depuis la source Math-Net.Ru

Voir la notice de l'article

When constructing control strategies for intelligent objects, the standard approach is to assume the rationality of their behavior. In some applications, however, a control object solves a collective problem within a group of other objects and, due to collective obligations, can or should act irrationally. This scenario becomes especially relevant when a group of different-type robotic means carries out a collective mission in an opposing environment under semi-autonomous or autonomous group control. This paper proposes an algorithm for forming a space-time structure of a swarm of mini-robots that is irrational for an external observer. A group of robots is treated as a multiagent system in which each agent is trained in the paradigm of collective behavior and motion within a swarm. The irrational behavior of robots is de need, and the conditions for switching from rational behavior to irrational one are considered. The approach is illustrated by an example of constructing special swarm formations consisting of several dozens of mini-robots (up to two hundred), the sizes of which are commensurate with the distance between them, carrying out a collective mission under an external observer opposing them. As shown below, such irrational formations can be created using a special modification of the Reynolds swarm algorithm.
Keywords: control object, swarm, robot, behavior, rationality, irrationality.
Mots-clés : group, agent 
@article{VSPUI_2021_17_4_a9,
     author = {V. K. Abrosimov and A. Yu. Mazurov},
     title = {Irrational behavioral strategies for a swarm of mini-robots},
     journal = {Vestnik Sankt-Peterburgskogo universiteta. Prikladna\^a matematika, informatika, processy upravleni\^a},
     pages = {419--432},
     year = {2021},
     volume = {17},
     number = {4},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/VSPUI_2021_17_4_a9/}
}
TY  - JOUR
AU  - V. K. Abrosimov
AU  - A. Yu. Mazurov
TI  - Irrational behavioral strategies for a swarm of mini-robots
JO  - Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ
PY  - 2021
SP  - 419
EP  - 432
VL  - 17
IS  - 4
UR  - http://geodesic.mathdoc.fr/item/VSPUI_2021_17_4_a9/
LA  - en
ID  - VSPUI_2021_17_4_a9
ER  - 
%0 Journal Article
%A V. K. Abrosimov
%A A. Yu. Mazurov
%T Irrational behavioral strategies for a swarm of mini-robots
%J Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ
%D 2021
%P 419-432
%V 17
%N 4
%U http://geodesic.mathdoc.fr/item/VSPUI_2021_17_4_a9/
%G en
%F VSPUI_2021_17_4_a9
V. K. Abrosimov; A. Yu. Mazurov. Irrational behavioral strategies for a swarm of mini-robots. Vestnik Sankt-Peterburgskogo universiteta. Prikladnaâ matematika, informatika, processy upravleniâ, Tome 17 (2021) no. 4, pp. 419-432. http://geodesic.mathdoc.fr/item/VSPUI_2021_17_4_a9/

[1] Endsley M. R., “Situation awareness misconceptions and misunderstandings”, Journal of Cognitive Engineering and Decision Making, 9:1 (2015), 4–32 | DOI

[2] Raikov A. N., “Accelerating decision-making in transport emergency with artificial intelligence”, Advances in Science, Technology and Engineering Systems Journal, 5:6 (2020), 520–530 | DOI

[3] Burenok V. M., “The directions and problems of applying artificial intelligence”, Intern. Conference “Artificial Intelligence. Problems and Solutions” (Moscow, 2018), 24–119

[4] Gorodetskii V. I., Grushinskii M. S., Kabalov A. V., “Multiagent systems (review)”, Artificial Intelligence News, 1998, no. 2, 64–116 (In Russian)

[5] Kalyaev I. A., Gaiduk A. R., Kapustyan S. G., Models and algorithms of collective control in robot groups, Fizmatlit Publ., M., 2009, 280 pp. (In Russian)

[6] Abrosimov V. K., Mochalkin A. N., Skobelev P. O., “A behavioral strategy of an autonomous robot in an opposing environment: Situational awareness and self-organization”, The 19$^{th}$ Intern. Conference “Complex Systems: Control and Modeling Problems”, Ofort-S Publ, Samara, 2017, 45–53

[7] Larichev O. I., Theory and methods of decision making, Logos Publ, M., 2000, 296 pp. (In Russian)

[8] Karpov V. E., Karpova I. P., Kulinich A. A., Social communities of robots, Lenand Publ, M., 2019, 352 pp. (In Russian)

[9] Rao A. S., Georgeff M. P., “BDI agents: From theory to practice”, The 1$^{st}$ Intern. Conference on Multi-Agent Systems (ICMAS–95) (San Francisco, USA, 1995), 312–319

[10] Czaplicka A., Chmieland A., Hołyst J. A., “Emotional agents at the square lattice”, Acta Physica Polonica A, 117:4 (2010), 688–694 | DOI

[11] Abrosimov V. K., Collectives of aircrafts, Nauka Publ, M., 2017, 304 pp. (In Russian)

[12] Reynolds C., “Flocks, herds, and schools: a distributed behavioral model”, Computer Graphics, 21:4 (1987), 25–34 | DOI

[13] Raikov A., Cognitive semantics of artificial intelligence: A new perspective, Springer Publ, Singapore, 2021, 110 pp. | DOI | Zbl

[14] Nu X., Eberhart R., “Solving constrained nonlinear optimization problems with particle swarm optimization”, The 6$^{th}$ World Multiconference on System Cybernetics and Informatics (Orlando, Florida, USA, 2002), 203–206

[15] Ruchkin K. A., Danilov A. V., “Design of a multi-agent system for predicting the behavior of a dynamic system in real time”, Artificial Intelligence, 2011, no. 4, 449–460

[16] Abrosimov V. K., “Role allocation in a group of control objects: general purpose approach”, Recent Developments in Intelligent Nature-Inspired Computing, IGI Global Publ, 2017, 206–224 | DOI

[17] Abrosimov V. K., “The property of agent's sacrifice: definition, measure, effect and applications”, Intern. Journal Reasoning-based Intelligent Systems, 8:1/2 (2016), 76–83 | DOI

[18] Pinciroli C., Beltrame G., “Buzz: An extensible programming language for heterogeneous swarm robotics”, 2016 IEEE/RSJ Intern. Conference on Intelligent Robots and Systems (IROS), 2016, 3794–3800 | DOI