A framework for the analysis and synthesis of Swarm Intelligence algorithms. Issue 4 (4th July 2021)

• Record Type: Journal Article
• Authors: Cruz, Dávila Patrícia Ferreira; Maia, Renato Dourado; de Castro, Leandro Nunes
• Is Part Of: Journal of experimental & theoretical artificial intelligence. Volume 33:Issue 4(2021)
• Page Start: 659
• Page End: 681
• Publication Date: 2021-07-04
• Subjects: Swarm Intelligence -- bio-inspired algorithms -- natural computing -- information processing -- decision-making -- social insects; Artificial intelligence -- Periodicals; 006.3
• DOI: 10.1080/0952813X.2020.1764635
• Languages: English
• ISSNs: 0952-813X

Abstract

ABSTRACT: 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.