Temat: Multi-agent systems - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Agent-based data integration framework
Autorzy:: Faber, Ł.
Powiązania:: https://bibliotekanauki.pl/articles/305369.pdf
Data publikacji:: 2014
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: data integration
multi-agent systems
Opis:: Combining data from diverse, heterogeneous sources while facilitating a unified access to it is an important (albeit difficult) task. There are various possibilities of performing it. In this publication, we propose and describe an agent-based framework dedicated to acquiring and processing distributed, heterogeneous data collected from diverse sources (e.g., the Internet, external software, relational, and document databases). Using this multi-agent-based approach in the aspects of the general architecture (the organization and management of the framework), we create a proof-of-concept implementation. The approach is presented using a sample scenario in which the system is used to search for personal and professional profiles of scientists.
Źródło:: Computer Science; 2014, 15 (4); 389-410
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Niching in evolutionary multi-agent systems
Autorzy:: Krzywicki, D.
Powiązania:: https://bibliotekanauki.pl/articles/305774.pdf
Data publikacji:: 2013
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: niching
evolutionary algorithms
multi-agent systems
Opis:: Niching is a group of techniques used in evolutionary algorithms, useful in several types of problems, including multimodal or nonstationary optimization. This paper investigates the applicability of these methods to evolutionary multi-agent systems (EMAS), a hybrid model combining the advantages of evolutionary algorithms and multi-agent systems. This could increase the efficiency of this type of algorithms and allow to apply them to a wider class of problems. As a starting point, a simple but flexible EMAS framework is proposed. Then, it is shown how to extend this framework in order to introduce niching, by adapting two classical niching methods. Finally, preliminary experimental results show the efficiency and the simultaneous discovery of multiple optima by this modified EMAS.
Źródło:: Computer Science; 2013, 14 (1); 77-95
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

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

Skocz do pozycji: 4.

Tytuł:: Evolutionary multi-agent systems in non-stationary environments
Autorzy:: Kisiel-Dorohinicki, M.
Powiązania:: https://bibliotekanauki.pl/articles/305810.pdf
Data publikacji:: 2013
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:: multi-agent systems
evolutionary computation
dynamic optimization
non-stationary environment
Opis:: In this article, the performance of an evolutionary multi-agent system in dynamic optimization is evaluated in comparison to classical evolutionary algorithms. The starting point is a general introduction describing the background, structure and behavior of EMAS against classical evolutionary techniques. Then, the properties of energy-based selection are investigated to show how they may influence the diversity of the population in EMAS. The considerations are illustrated by experimental results based on the dynamic version of the well-known, high-dimensional Rastrigin function benchmark.
Źródło:: Computer Science; 2013, 14 (4); 563-575
1508-2806
2300-7036
Pojawia się w:: Computer Science
Dostawca treści:: Biblioteka Nauki

Artykuł

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