Szczegóły publikacji
Opis bibliograficzny
Autonomous hybridization of agent-based computing / Mateusz GODZIK, Michał IDZIK, Kamil PIĘTAK, Aleksander BYRSKI, Marek KISIEL-DOROHINICKI // W: Computational collective intelligence : 12th International Conference, ICCCI 2020, Da Nang, Vietnam, November 30–December 3, 2020 : proceedings / eds. Ngoc Thanh Nguyen, [et al.]. — Cham : Springer Nature Switzerland AG, cop. 2020. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12496. Lecture Notes in Artificial Intelligence). — ISBN: 978-3-030-63006-5; e-ISBN: 978-3-030-63007-2. — S. 139–151. — Bibliogr., Abstr.
Autorzy (5)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 131578 |
|---|---|
| Data dodania do BaDAP | 2020-12-22 |
| DOI | 10.1007/978-3-030-63007-2_11 |
| Rok publikacji | 2020 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computational Collective Intelligence: Semantic Web, Social Networks and Multiagent Systems 2020 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
Using agent-based systems for computing purposes, where agent becomes not only driver for realizing computing task, but a part of the computing itself is an interesting paradigm allowing for easy yet robust design of metaheuristics, making possible easy parallelization and developing new efficient computing methods. Such methods as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO) or Evolutionary Multi Agent-System (EMAS) are examples of such algorithms. In the paper novel approach to hybridization of such computing systems is presented. A number of agents doing their computing task can agree to run other algorithm (similarly to high level hybrid proposed by Talbi). The paper focuses on presenting the background and the idea of such algorithm along with firm experimental results. © 2020, Springer Nature Switzerland AG.
