Optimisation plays a fundamental role in the design and learning of fuzzy systems and their integration with modern machine learning pipelines. From early heuristic and evolutionary approaches to recent differentiable and gradient-based methods, ongoing advances continue to enhance the accuracy, scalability, and interpretability of fuzzy modelling, control, and decision support.
This Special Session aims to provide a focused forum for presenting recent advances in optimisation for fuzzy systems, covering both gradient-based and non-gradient-based techniques. It will explore methodological innovations, algorithmic developments, and practical applications that push the boundaries of fuzzy system learning and adaptation.
Particular attention will be given to Automatic Differentiation (AD) and differentiable programming frameworks, which enable efficient and exact gradient computation for fuzzy systems, alongside comparative studies with heuristic and evolutionary optimisation. Contributions are welcome on novel methods, hybrid optimisation strategies, software implementations, open benchmarks and reproducible software packages, and real-world applications across diverse domains such as control, prediction, and intelligent decision-making.
Topics of interest include (but are not limited to):
Paper Submission Deadline: January 31, 2026 (AoE)
Final Decision Notification to Authors: March 15, 2026 (AoE)
Camera-Ready Submission Deadline: April 15, 2026 (AoE)
For more details, please refer to the WCCI submission instructions. Note all submissions should go through WCCI submission portal and will go the normal peer-review process.
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