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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Bibliographic Details
Published inJournal of experimental & theoretical artificial intelligence Vol. 33; no. 4; pp. 659 - 681
Main Authors Cruz, Dávila Patrícia Ferreira, Maia, Renato Dourado, de Castro, Leandro Nunes
Format Journal Article
LanguageEnglish
Published Abingdon Taylor & Francis 04.07.2021
Taylor & Francis Ltd
Subjects
Algorithms
bio-inspired algorithms
decision-making
information processing
Insects
Metaphor
natural computing
social insects
Swarm Intelligence
Synthesis
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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.
ISSN:0952-813X
1362-3079
DOI:10.1080/0952813X.2020.1764635