Content

Soft computing offers a rich set of techniques—such as fuzzy logic, neuro-computing, probabilistic reasoning, and evolutionary methods—that enable the modeling and analysis of systems characterized by uncertainty, partial information, and structural complexity. As many real-world problems increasingly involve imprecision and dynamically changing data, these approaches have become essential for building flexible, robust, and interpretable intelligent systems.

In the context of a conference focused on rough sets, the synergy between soft computing, fuzzy logic, and rough set theory provides powerful foundations for handling vagueness, constructing hybrid models, and developing reliable decision-support mechanisms. Exploring these connections is key to advancing both theoretical research and practical solutions.

This special session invites contributions addressing recent advances, new theoretical developments, hybrid approaches, explainable models, and empirical studies that demonstrate the problem-solving advantages of soft computing. Papers integrating fuzzy logic and rough sets, proposing new algorithms, or applying soft computing techniques to complex real-world domains are especially welcome.

Keywords and Topics

• Fuzzy logic and fuzzy systems
• Hybrid fuzzy–rough set models
• Neuro-computing and fuzzy learning
• Probabilistic and evolutionary computation
• Reasoning and decision-making under uncertainty
• Explainable intelligent systems based on soft computing
• Applications in digital health, digital economy, and complex service systems
• Natural language processing with soft computing techniques
• Software tools and platforms for soft computing

Organizers

• Javier Cabrerizo, University of Granada, Spain
• Bernard De Baets, University of Ghent, Belgium
• Ondrej Krejcar, University of Hradec Kralove, Czech Republic
• Ignacio J. Pérez Gálvez, University of Granada, Spain