Szczegóły publikacji
Opis bibliograficzny
Learning in a multi-agent system as a mean for effective resource management / Bartłomiej ŚNIEŻYŃSKI, Jarosław KOŹLAK // W: Computational Science – ICCS 2006 : 6th International Conference reading : UK, May 28–31, 2006 : proceedings , Pt. 3 / eds. Vassil N. Alexandrov [et al.]. — Berlin ; Heidelberg : Springer-Verlag, 2006. — ( Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 3993. Theoretical Computer Science and General Issues ; ISSN 0302-9743 ). — ISBN: 978-3-540-34383-7; ISBN: 3-540-34383-0; e-ISBN: 978-3-540-34384-4. — S. 703–710. — Bibliogr. s. 710, Abstr. — Toż na CD-ROMie
Autorzy (2)
Dane bibliometryczne
| ID BaDAP | 29377 |
|---|---|
| Data dodania do BaDAP | 2006-10-12 |
| DOI | 10.1007/11758532_92 |
| Rok publikacji | 2006 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
In this paper symbolic, supervised learning is used in a multiagent system for resource management. Environment is a Fish Bank game, where agents manage fishing companies. Rule induction is applied to generate ship allocation and cooperation rules. In this article system architecture and learning process are described and experimental results comparing performance of several types of agents are presented. The results obtained confirm that applying a supervised learning algorithm in a multi-agent system may improve resource management. © Springer-Verlag Berlin Heidelberg 2006.
