Szczegóły publikacji
Opis bibliograficzny
$(\mu + \lambda)$ Evolution Strategy with socio-cognitive mutation / Aleksandra URBAŃCZYK, Krzysztof Kucaba, Mateusz WOJTULEWICZ, Marek KISIEL-DOROHINICKI, Leszek RUTKOWSKI, Piotr Duda, Janusz KACPRZYK, Xin Yao, Siang Yew Chong, Aleksander BYRSKI // Journal of Automation, Mobile Robotics & Intelligent Systems : JAMRIS ; ISSN 1897-8649 . — 2024 — vol. 18 no. 1, s. 1–11. — Bibliogr. s. 9–11, Abstr. — L. Rutkowski, J. Kacprzyk - dod. afiliacja: Institute of Systems ScienceResearch, Warsaw, Poland
Autorzy (10)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 152789 |
|---|---|
| Data dodania do BaDAP | 2024-05-13 |
| Tekst źródłowy | URL |
| DOI | 10.14313/JAMRIS/1-2024/1 |
| Rok publikacji | 2024 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Automation, Mobile Robotics and Intelligent Systems |
Abstract
Socio-cognitive computing is a paradigm developed for the last several years in our research group. It consists of introducing mechanisms inspired by inter-individual learning and cognition into metaheuristics. Different versions of the paradigm have been successfully applied in hybridizing Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Genetic Algorithms, Differential Evolution, and Evolutionary Multi-agent System (EMAS) metaheuristics. In this paper, we have followed our previous experiences in order to propose a novel mutation based on sociocognitive mechanism and test it based on Evolution Strategy (ES). The newly constructed versions were applied to popular benchmarks and compared with their reference versions.
