Szczegóły publikacji
Opis bibliograficzny
Co-evolutionary multi-agent system with predator-prey mechanism for multi-objective optimization / Rafał DREŻEWSKI, Leszek SIWIK // W: Adaptive and natural computing algorithms : 8th international conference, ICANNGA 2007 : Warsaw, Poland, April 11–14, 2007 : proceedings , Pt. 1 / eds. Bartlomiej Beliczynski, [et al.]. — Berlin ; Heidelberg : Springer-Verlag, 2007. — ( Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 4431. Theoretical Computer Science and General Issues ; ISSN 0302-9743 ). — ISBN: 978-3-540-71589-4; ISBN: 3-540-71589-4. — S. 67–76. — Bibliogr. s. 75–76, Abstr. — Toż: W: Adaptive and natural computing algorithms [Dokument elektroniczny] : ICANNGA 2007 : 8th international conference : Warsaw, Poland, April 11–14, 2007 : proceedings. — Wersja do Windows. — Dane tekstowe. — [Berlin ; Heidelberg] : Springer, cop. 2007. — 1 dysk optyczny. — (LNCS 4431) ; (LNCS 4432). — ISBN 978-3-540-71589-1 ; ISBN 978-3-540-71590-0. — [Part 1 and 2]. — S. [1–10]. — Wymagania systemowe Adobe Acrobat Reader ; napęd CD-ROM. — Bibliogr. s. [9–10]
Autorzy (2)
Dane bibliometryczne
| ID BaDAP | 36472 |
|---|---|
| Data dodania do BaDAP | 2008-01-21 |
| DOI | 10.1007/978-3-540-71618-1_8 |
| Rok publikacji | 2007 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
Co-evolutionary techniques for evolutionary algorithms allow for the application of such algorithms to problems for which it is difficult or even impossible to formulate explicit fitness function. These techniques also maintain population diversity, allows for speciation and help overcoming limited adaptive capabilities of evolutionary algorithms. In this paper the idea of co-evolutionary multi-agent system with predator-prey mechanism for multi-objective optimization is introduced. In presented system the Pareto frontier is located by the population of agents as a result of co-evolutionary interactions between two species: predators and prey. Results from runs of presented system against test problem and comparison to classical multi-objective evolutionary algorithms conclude the paper.
