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Type: Article
Title: Application of Evolutionary Artificial Intelligence. An Exploratory Literature Review PDF Article,
Author: Nijole Maknickiene
On-line: 31-August-2022
Metrics: Applied Business: Issues & Solutions 1(2022)22-31 – ISSN 2783-6967.
DOI: 10.57005/ab.2022.1.4
Abstract. Evolutionary processes found in nature are of interest to developers and practitioners of artificial intelligence because of the ability to optimize, detect, classify, and predict complex man-made processes. Evolutionary artificial intelligence (EAI) is examined from various perspectives to evaluate the main research directions and the trend of the decade. Co-occurrence networks were used to visualize data and find key sub-themes in a dataset consisting of article titles. The literature review covers the following aspects of EAI applications: methods, detection, data, approach, and colony. The resulting co-occurrence networks show a huge increase in diversity in research methods, data and function application possibilities, and approaches. Although simulating the behaviour of colonies is not as popular as it was a decade ago, the scope of applications for known algorithms has not been diminished.
JEL: C6; C8.
Keywords: colony; co-occurrence network; detection; differential evolution; evolution; multi-objective optimization; swarm intelligence.
Citation: Nijole Maknickiene (2022) Application of Evolutionary Artificial Intelligence. An Exploratory Literature Review. – Applied Business: Issues & Solutions 1(2022)22-31 – ISSN 2783-6967.

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