Szczegóły publikacji

Opis bibliograficzny

An individual approach to robot swarm modelling / Waldemar RĄCZKA, Dorota MARSZALIK // W: 27th International Carpathian Control Conference (ICCC) [Dokument elektroniczny] : 1-3 June 2026, Szilvásvárad, Hungary : proceedings. — Wersja do Windows. — Dane tekstowe. — Piscataway : IEEE, cop. 2026. — Print on Demand(PoD) ISBN: 979-8-3195-3321-0. — e-ISBN: 979-8-3195-3320-3. — S. 443–448. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 448, Abstr. — Publikacja dostępna online od: 2026-07-07

Autorzy (2)

Słowa kluczowe

agentsswarmrobotsmodel

Dane bibliometryczne

ID BaDAP169798
Data dodania do BaDAP2026-10-06
Tekst źródłowyURL
DOI10.1109/ICCC71363.2026.11593177
Rok publikacji2026
Typ publikacjimateriały konferencyjne (aut.)
Otwarty dostęptak
WydawcaInstitute of Electrical and Electronics Engineers (IEEE)

Abstract

A swarm, herd, or school is a naturally occurring formation that has long inspired researchers. These formations display intrinsic cooperation, self-organization, and adaptability to changing environmental conditions. Mathematical swarm models attempt to describe such behaviors in various ways, often drawing on biological inspiration and the observation that a swarm consists of numerous individuals that communicate and coordinate to achieve collective patterns of motion. In many cases, the purpose of this collective behavior is not immediately apparent, as in the autumnal flocking of birds, and it is very fascinating. The inner dynamics of a swarm arise from fundamental principles such as local interactions, continuous adaptation, and self-organization. This article presents an approach to modeling swarm behavior in which the swarm is not treated as a separate modeling entity but instead emerges from mechanisms embedded within individual agents. A mathematical model of a single agent is introduced, and the swarm results from the interaction of many such agents. The paper describes the internal mechanisms governing each agent and presents the outcomes of simulations based on this model.

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