Szczegóły publikacji
Opis bibliograficzny
Socio-cognitive evolution strategies / Aleksandra URBAŃCZYK, Bartosz Nowak, Patryk ORZECHOWSKI, Jason H. Moore, Marek KISIEL-DOROHINICKI, Aleksander BYRSKI // W: Computational Science – ICCS 2021 : 21st international conference : Krakow, Poland, June 16–18, 2021 : proceedings, Pt. 2 / eds. Maciej Paszyński, [et al.]. — Cham : Springer Nature Switzerland, cop. 2021. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12743. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-030-77963-4; e-ISBN: 978-3-030-77964-1. — S. 329–342. — Bibliogr., Abstr. — Publikacja dostępna online od: 2021-06-09. — P. Orzechowski - dod. afiliacja: University of Pennsylvania, Philadelphia, USA
Autorzy (6)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 134721 |
|---|---|
| Data dodania do BaDAP | 2021-07-28 |
| DOI | 10.1007/978-3-030-77964-1_26 |
| Rok publikacji | 2021 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | 21st International Conference on Computational Science |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
Socio-cognitive computing is a paradigm developed for the last several years, it consists in introducing into metaheuristics mechanisms inspired by inter-individual learning and cognition. It was successfully applied in hybridizing ACO and PSO metaheuristics. In this paper we have followed our previous experiences in order to hybridize the acclaimed evolution strategies. The newly constructed hybrids were applied to popular benchmarks and compared with their referential versions.