TY - JOUR

T1 - Emergent Intelligence via Self-Organization in a Group of Robotic Devices

AU - Amelin, Konstantin

AU - Granichin, Oleg

AU - Sergeenko, Anna

AU - Volkovich, Zeev V.

N1 - Funding Information: Funding: The Sections 1–3 were supported by the St. Petersburg State University (project No. 73555239). The Section 4 was supported by the Ministry of Science and Higher Education of the Russian Federation (Project No. 075-15-2021-573, IPME RAS). Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/6/8

Y1 - 2021/6/8

N2 - Networked systems control is a known problem complicated because of the need to work with large groups of elementary agents. In many applications, it is impossible (or difficult) to validate agent movement models and provide sufficiently reliable control actions at the elementary system components level. The evolution of agent subgroups (clusters) leads to additional uncertainty in the studied control systems. We focus on new decentralized control methods based on local communications in complex multiagent dynamical systems. The problem of intelligence in a complex world is considered in connection to multiagent network systems, including a system named airplane with feathers, load balancing, and the multisensor-multitarget tracking problem. Moreover, the new result concerning the emergency of intelligence in a group of robots is provided. All these methods follow the paradigm of the direct reaction of each element (agent) of the system to its sensory data of current situation observations and the corresponding data from a limited number of its neighbors (local communications). At the same time, these algorithms achieve a mutual goal at the macro level. All of the considered emergent intelligence appearances inspire the necessity to "rethink" the previously recognized concepts of computability and algorithm in computer science.

AB - Networked systems control is a known problem complicated because of the need to work with large groups of elementary agents. In many applications, it is impossible (or difficult) to validate agent movement models and provide sufficiently reliable control actions at the elementary system components level. The evolution of agent subgroups (clusters) leads to additional uncertainty in the studied control systems. We focus on new decentralized control methods based on local communications in complex multiagent dynamical systems. The problem of intelligence in a complex world is considered in connection to multiagent network systems, including a system named airplane with feathers, load balancing, and the multisensor-multitarget tracking problem. Moreover, the new result concerning the emergency of intelligence in a group of robots is provided. All these methods follow the paradigm of the direct reaction of each element (agent) of the system to its sensory data of current situation observations and the corresponding data from a limited number of its neighbors (local communications). At the same time, these algorithms achieve a mutual goal at the macro level. All of the considered emergent intelligence appearances inspire the necessity to "rethink" the previously recognized concepts of computability and algorithm in computer science.

KW - Consensus

KW - Emergent artificial intelligence

KW - Multiagent technologies

KW - Robot

KW - consensus

KW - robot

KW - multiagent technologies

KW - MULTIAGENT

KW - TRACKING

KW - emergent artificial intelligence

UR - http://www.scopus.com/inward/record.url?scp=85108252320&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/b41776ce-641a-330d-8e1b-b4a90ad10ade/

U2 - 10.3390/math9121314

DO - 10.3390/math9121314

M3 - статья

AN - SCOPUS:85108252320

VL - 9

JO - Mathematics

JF - Mathematics

SN - 2227-7390

IS - 12

M1 - 1314

ER -