AI-Driven Fractal Models for Complex Systems

Dear Colleagues,

Complex systems often exhibit fractal-like properties, such as self-similarity and scale invariance, which reveal hidden patterns in their structure and dynamics. This Special Issue explores the intersection of fractal models and AI techniques—such as reinforcement learning, graph neural networks, and generative models—to improve our understanding of and ability to predict the behaviour of complex systems. By integrating fractal analysis with AI, we aim to uncover multi-scale patterns, enhance predictive capabilities, and develop innovative tools for modelling the evolving dynamics of areas like social behaviour, community detection, and network analysis. We encourage contributions that bridge fractal theory with emerging AI techniques, particularly graph representation learning, decision-making methods, generative models, and large language models (LLMs), fostering interdisciplinary advancements in the study of complex systems in the new AI era. This Special Issue will cover the following topics, among others:

• Fractal and AI methods for community detection;
• Fractal and AI methods for network prediction, evolution, and control;
• Fractal and AI methods for information propagation in social networks;
• Fractal and AI methods for human behaviour and social system analysis;
• AI-driven fractal methods for decision making, game theory, and market design;
• Fractal models for decision-making processes in complex systems;
• AI-driven fractal methods for FinTech and finance prediction;
• AI-based fractal methods for NLP and cross-lingual studies in online networks;
• Fractal patterns in linguistic structures and their application to LLMs;
• Fractal and AI for semantic network and language complexity;
• Fractal and AI for language sentiment analysis;
• Fractal methods for reinforcement learning;
• Fractal analysis for graph neural networks;
• Fractal analysis for time-series analysis and prediction.

Dr. Dong Hao
Prof. Dr. María A. Navascués
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. Fractal and Fractional 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 2700 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.

• fractal model and AI for social network and human behaviour
• fractal AI models in economic and finance
• AI-based fractal models for LLMS and NLP systems
• intersection of fractal models and machine learning