Modeling Complex Interactions Beyond Networks

Dear Colleagues,

Complex systems emerge from the collective behavior of many interacting components, often exhibiting non-trivial, adaptive, and self-organizing dynamics. Classical examples range from ecosystems and neural circuits to social and technological infrastructures. In recent years, the study of such systems has expanded beyond the traditional graph theory in order to include hypergraphs (which capture multi-way dependencies in the form of group interactions) and multiplex networks (which encode interconnected layers of relationships), thereby allowing for a richer and more accurate representation of real-world interactions and systems. Hypergraphs model multi-way relationships, which are essential in contexts like biochemical networks and co-authorship relations, while multiplex networks capture different types of interactions among the same sets of entities, which are crucial for social and transportation systems.

The integration of information–theoretic approaches with these enriched network models opens new avenues for characterizing dynamics, correlations, and emergent behaviors in complex systems. This line of research is vital for both theoretical development and practical applications in fields such as AI, biology, and cognitive sciences.

Key challenges include characterizing non-linear dependencies, scaling computational methods for large systems, and linking structural patterns with dynamic behavior. Applications span diverse domains, including deep learning, where architecture design and training dynamics can be viewed as complex systems problems, as well as biological networks, social networks, and adaptive infrastructure.

This Special Issue seeks contributions on theoretical and applied studies of complex systems, particularly those leveraging hypergraphs, multiplex networks, and higher-order modeling, to advance our understanding and control of real-world interconnected systems.

Prof. Dr. José F.F. Mendes
Prof. Dr. Matjaz Perc
Guest Editors

Manuscript Submission Information

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• complex systems
• hypergraphs
• multiplex networks
• deep learning
• self-organizing dynamics
• social networks
• biological networks
• adaptive infrastructure networks
• higher-order networks