Szczegóły publikacji
Opis bibliograficzny
Agent strategy generation by rule induction in predator-prey problem / Bartłomiej ŚNIEŻYŃSKI // W: Computational Science – ICCS 2009 [Dokument elektroniczny] : 9th international conference : Baton Rouge, LA, USA, May 25–27, 2009 : proceedings, Pt. 1–2 / eds. Gabrielle Allen [et al.]. — Wersja do Windows. — Dane tekstowe. — Berlin ; Heidelberg : Springer-Verlag, cop. 2009. — 1 dysk optyczny. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 5544, LNCS 5545). — e-ISBN: 978-3-642-01969-2; e-ISBN: 3-642-01969-2. — S. 895–903. — Wymagania systemowe: Adobe Reader ; napęd CD-ROM. — Bibliogr. s. 902–903, Abstr. — Publikacja zmieszczona w Pt. 2
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 46117 |
|---|---|
| Data dodania do BaDAP | 2009-08-04 |
| DOI | 10.1007/978-3-642-01973-9_99 |
| Rok publikacji | 2009 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
This paper contains a proposal of application of rule induction for generating agent strategy. This method of learning is tested on a predator-prey domain, in which predator agents learn how to capture preys. We assume that proposed learning mechanism will be beneficial in all domains, in which agents can determine direct results of their actions. Experimental results show that the learning process is fast. Multi-agent communication aspect is also taken into account. We can show that in specific conditions transferring learned rules gives profits to the learning agents.
