Complex Networks, Evolutionary Computation and Machine Learning

Dear Colleagues,

This Special Issue focuses on the broad topic of “Complex Networks, Evolutionary Computation, and Machine Learning”. On the one hand, many natural and real-world systems can be modeled as complex networks and then studied using network analysis tools, evolutionary computation, and machine learning techniques. On the other hand, the development of complex network studies provides alternative ideas and tools for evolutionary computation and machine learning.

We invite you to submit your latest research in the area of complex networks and computational intelligence to this Special Issue. Theoretical and empirical articles on the application of novel complex networks, evolutionary computation, and machine learning in modeling, estimation, prediction, simulation, and optimization, as well as their applications to real-world problems are welcome. High-quality papers are solicited to address both theoretical and practical issues of complex networks, evolutionary computation, and/or machine learning. Potential topics include but are not limited to, for example, using evolutionary computation and/or machine learning to solve large-scale complex network problems, network problem-based methodology for computational techniques, etc.

Dr. Yang (Felix) Lou
Prof. Dr. Guanrong (Ron) Chen
Prof. Dr. Lin Wang
Guest Editors

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 special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

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. Axioms 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 2400 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.