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Memetic Computing
Erschienen in: Memetic Computing 1/2015

01.03.2015 | Regular research paper

A computational ecosystem for optimization: review and perspectives for future research

verfasst von: Rafael Stubs Parpinelli, Heitor Silvério Lopes

Erschienen in: Memetic Computing | Ausgabe 1/2015

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Abstract

Nature exhibits extremely diverse, dynamic, robust, complex and fascinating phenomena and, since long ago, it has been a great source of inspiration for solving hard and complex problems in computer science. Hence, the search for plausible biologically inspired ideas, models and computational paradigms always drew the interest of computer scientists. It is worth mentioning that most bio-inspired algorithms only focuses on and took inspiration from specific aspects of the natural phenomena. However, in nature, biological systems are interlinked to each other, e.g., biological ecosystems. The ecosystem as a whole can be composed by species that respond to environmental and ecological stimuli. This work reviews the theoretical foundations and applications of a computational ecosystem for optimization, named ECO. Also, as some concepts and processes inherent to biological ecosystems have already been explored in the ECO approach, some related works are described. Finally, several future research directions are pointed.
Vorheriger Artikel Group based Swarm evolution algorithm (GSEA) driven mental task classifier
Nächster Artikel A BBO based framework for natural terrain identification in remote sensing

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Fußnoten
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Metadaten
Titel
A computational ecosystem for optimization: review and perspectives for future research
verfasst von
Rafael Stubs Parpinelli
Heitor Silvério Lopes
Publikationsdatum
01.03.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
Memetic Computing / Ausgabe 1/2015
Print ISSN: 1865-9284
Elektronische ISSN: 1865-9292
DOI
https://doi.org/10.1007/s12293-014-0148-4

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