Special Issue on IEEE Computational Intelligence Magazine

Computational Intelligence (CI) provides a set of powerful tools to effectively tackle complex computational tasks: global optimization methods (e.g., evolutionary computation, swarm intelligence), machine learning (e.g., neural networks), and fuzzy reasoning. 

While CI research activity generally focuses on the improvement of the algorithms (e.g., faster convergence, higher accuracy, reduced error), there is another promising research direction consisting in the modification of the representation of solutions. 

Prof. Qu, Ashlock, Manzoni and me will be Guest Editors of a Special Issue on IEEE Computational Intelligence Magazine (CIM) exactly focused on the “representation” topic, in the widest sense:

https://cmte.ieee.org/cis-bbtc/ieee-cim-special-issue-on-models-of-representation-in-computational-intelligence/

This special issue aim at collecting research work introducing novel ideas in multiple areas:

• For evolutionary and population-based techniques, new variation operators and even new classes of global optimization meta-heuristics that might devote a part of their budget for fitness evaluations to automatically derive an optimal representation.
• New general techniques for the manipulation (e.g., shrinking, stretching, remapping) of the search space for a particular class of problems might be used to improve the performances and generality of most existing CI methods in that particular class of problems.
• Deep learning is capable of sophisticated pattern recognition using many layers of neural processing to extract more and more complex features.  This suggests that deep learning could be employed to steer the process of self-organization of novel representations, abstracting the portions of the representational domain that yield better performance.
• This special issue is open to both novel directions on transforming problems (to make them easier to solve, or clear to interpret/analyse) or radically new algorithms (e.g., novel generative or implicit representations). 
• From the point of view on interpretable and explainable AI, new theories about representation and communication can arise, providing domain experts with an increased level of understandability of the CI system.

The deadline for the submission is June 1st. Submit your research!