<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

Published Online: Dec 31, 2018

Page range: 81 - 97

Received: Jan 18, 2018

Accepted: May 10, 2018

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

Keywords
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

Published Online: Dec 31, 2018

Page range: 81 - 97

Received: Jan 18, 2018

Accepted: May 10, 2018

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

Keywordsmulti-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.

Keywords
multi-agent systems, metaheuristics, evolutionary computing