Feature Papers in Evolutionary Algorithms and Machine Learning
A topical collection in Algorithms (ISSN 1999-4893). This collection belongs to the section "Evolutionary Algorithms and Machine Learning".
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Topical Collection Information
Dear Colleagues,
This Topical Collection focuses on the intersection of evolutionary algorithms and machine learning, bringing together recent advancements in optimization, automated learning, and intelligent systems. Evolutionary algorithms, inspired by natural selection, have proven to be powerful methods for tackling complex optimization and learning problems. Their integration with machine learning techniques has led to innovative solutions in feature selection, neural architecture search, reinforcement learning, and many other domains.
We invite high-quality contributions that explore novel methodologies, theoretical insights, and real-world applications at the interface of evolutionary algorithms and machine learning. Topics of interest include, but are not limited to, the methodological development and practical application of the following:
- Evolutionary Algorithms for Machine Learning
- Genetic algorithms, genetic programming, evolutionary strategies, and swarm intelligence.
- Neuroevolution and neural architecture search (NAS).
- Machine Learning for Evolutionary Algorithms
- Surrogate-assisted evolutionary optimization.
- Transfer learning and evolutionary strategies.
- Hybrid and Advanced Techniques
- Memetic algorithms and hybrid evolutionary approaches.
- Bio-inspired computation and learning paradigms.
Prof. Dr. Stefano Mariani
Collection Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the collection website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Algorithms is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- evolutionary algorithms
- artificial intelligence
- machine and deep learning
