A framework for the analysis and synthesis of Swarm Intelligence algorithms
Over the last decades, the number of Swarm Intelligence algorithms proposed in the literature has increased considerably. However, most algorithms do not follow an adequate scientific rigour neither the principles of Swarm Intelligence, reproducing similar computational procedures of many other appr...
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Published in | Journal of experimental & theoretical artificial intelligence Vol. 33; no. 4; pp. 659 - 681 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Abingdon
Taylor & Francis
04.07.2021
Taylor & Francis Ltd |
Subjects | |
Online Access | Get full text |
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Summary: | Over the last decades, the number of Swarm Intelligence algorithms proposed in the literature has increased considerably. However, most algorithms do not follow an adequate scientific rigour neither the principles of Swarm Intelligence, reproducing similar computational procedures of many other approaches, but by means of a different metaphor. In this scenario, the aim of this paper is to propose a framework for the analysis and synthesis of Swarm Intelligence algorithms that can contribute to a structured understanding (analysis) and development (synthesis) of these algorithms. The main objective of the proposed framework is to guide the construction of Swarm Intelligence metaphors in a consistent and well-founded way, as well as to contribute with the analysis and development of new algorithms that had better encompass the features and abilities of insects' societies. |
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ISSN: | 0952-813X 1362-3079 |
DOI: | 10.1080/0952813X.2020.1764635 |