<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.</p></abstract>

Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.

Fine Tuning of Agent-Based Evolutionary Computing

Department of Computer Science, Faculty of Computer Science, Electronics and Telecommunications

Journal of Artificial Intelligence and Soft Computing Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Fine Tuning of Agent-Based Evolutionary Computing"}

Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a...

Fine Tuning of Agent-Based Evolutionary Computing

Publicado en línea: 31 dic 2018

Páginas: 81 - 97

Recibido: 18 ene 2018

Aceptado: 10 may 2018

DOI: https://doi.org/10.2478/jaiscr-2018-0026

Palabras clave
multi-agent systems, metaheuristics, evolutionary computing

© 2018 Michal Mizera et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Fine Tuning of Agent-Based Evolutionary Computing

Publicado en línea: 31 dic 2018

Páginas: 81 - 97

Recibido: 18 ene 2018

Aceptado: 10 may 2018

DOI: https://doi.org/10.2478/jaiscr-2018-0026

Palabras clavemulti-agent systems, metaheuristics, evolutionary computing

© 2018 Michal Mizera et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Palabras clave
multi-agent systems, metaheuristics, evolutionary computing