Autor: Byrski, A. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Towards an Agent-Based Augmented Cloud
Autorzy:: Dębski, R.
Byrski, A.
Kisiel-Dorohinicki, M.
Powiązania:: https://bibliotekanauki.pl/articles/308495.pdf
Data publikacji:: 2012
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: Agent Platform as a Service
Augmented Cloud
cloud computing
multi-agent systems
Opis:: In the paper an agent-based framework deployed in hybrid cluster and volunteer computing environment is presented. It utilizes two concepts proposed by the authors: Augmented Cloud and Agent Platform as a Service (AgPaaS). Both concepts are discussed in the context of Cloud Computing as defined by NIST. The key idea of the presented solution is to span the cloud (i.e., computing infrastructure) beyond the data center borders by utilizing web browsers as computational workers. The feasibility of the approach was demonstrated by two prototypes: the first one was based on Java Applets and Adobe Flash, whereas the second one on Microsoft Silverlight. The prototypes were next used to perform simple experiments, mainly related to scalability issues. Selected results from the experiments are discussed in the final part of the paper.
Źródło:: Journal of Telecommunications and Information Technology; 2012, 1; 16-22
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Evolutionary multi-agent computing in inverse problems
Autorzy:: Wróbel, K.
Torba, P.
Paszyński, M
Byrski, A.
Powiązania:: https://bibliotekanauki.pl/articles/305816.pdf
Data publikacji:: 2013
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: multi-agent systems
evolutionary computation
inverse problems
Opis:: This paper tackles the application of evolutionary multi-agent computing to solve inverse problems. High costs of fitness function call become a major difficulty when approaching these problems with population-based heuristics. However, evolutionary agent-based systems (EMAS) turn out to reduce the fitness function calls, which makes them a possible weapon of choice against them. This paper recalls the basics of EMAS and describes the considered problem (Step and Flash Imprint Lithography), and later, shows convincing results that EMAS is more effective than a classical evolutionary algorithm.
Źródło:: Computer Science; 2013, 14 (3); 367-383
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Informacja