Artificial Intelligence in Network Science

Dear Colleagues,

Recent interests in network data with multilayer and heterogeneous structures pose a significant challenge to traditional graph-theoretic and statistical approaches that have played important roles in network science. These multiplex and heterogeneous networks naturally arise in many research fields and industrial practices such as computational biology, social media, and knowledge graphs.   To address the challenge, techniques and models in Artificial Intelligence have the potential (and are increasingly being used) to complement traditional approaches to network analysis or to help solve algorithmic and computational problems that are beyond the reach of those more standard approaches.

This Special Issue is dedicated to showcasing recent progress in applying AI techniques to the analysis and modeling of complex networks.  All papers are welcome that describe work on using AI techniques in a substantial way to solve algorithmic problems in network analysis (such as those related to centrality measures, meso-scale structures, network embedding, role analysis, and network diffusion), to model network phenomena and evolution, or to understand the dynamic processes taking place on networks.  Of particular interest are papers that report original work on the use of AI problem-solving methods, deep representation learning techniques, and game-theoretic models to address problems in the analysis of multiplex networks and in the integration of networked data.   

Dr. Yong Gao
Dr. James Nastos
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 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.

• network science
• multiplex networks
• meso-scale structures
• network embedding
• dynamics and evolution of complex networks
• problem-solving methods
• reasoning and search
• graph representation learning
• deep learning
• integration of networked data