(Part of Cross-disciplinary & Applications Sessions at IEEE World Congress on Computational Intelligence 2020)
Computational Intelligence (CI), originally represented by the three subjects of Evolutionary Computation (EC), Fuzzy Logic (FL) and Neural Networks (NNs), has significantly evolved to date and reached high levels of hybridisation and complexity. Starting from fuzzy neural or genetic systems, to the more recent computational frameworks such as deep learning and natural learning processing, the subject of CI has widened and grown to traverse many disciplines and application domains. At the same time, this growth has made evident the lack of consistent theoretical knowledge based on which practitioners could control CI systems and have them express their full potential while addressing the real-world scenarios.
This means that in practice, high performance and quality of results are only achievable if theoretical CI community concentrates on filling the gaps in theoretical knowledge and CI practitioners put latest developments to use in their applications to address practical problems. Thus, through informed use of CI methods synergetically tailored to the problem at hand, on the base of the available theoretical knowledge, practitioners can suggest novel theoretically backed up solutions to benefit their applications. Indeed, following this research philosophy, ad-hoc CI solutions are currently being successfully created in the most heterogeneous fields, such as e.g. finance, medicine, precision agriculture and aviation, as well as in numerous information systems.
AIM AND SCOPE
This SS aims at attracting the latest results from researchers working on advances in CI. These results can stem from the generation of new theoretical knowledge on the discipline itself, or via the informed design of customised CI solutions to solve high-impact (e.g. humanitarian, environmental or economical) applications. Submissions are welcome on the following topics of interest (but are not limited to):
• Algorithmic Behaviour
• Stocastic & Metaheuristic Optimisation
• Genetic Fuzzy Systems
• Fuzzy Neural Systems
• Convolutional Neural Computing
• Foundations of optimisation
• Theoretical analysis and hybridisations in CI
• Connections of CI with Machine Learning
• Algorithm configuration and hyperparameter optimisation
• Algorithm selection
• Explainable Artificial Intelligence
• Neuroevolution
• Decision Making/Consensus Modelling in Social Networks
•Opinion Evolution
Applications in
INFORMATION FOR THE AUTHORS
Papers submitted to this Special Session are reviewed according to the same rules as the submissions to the regular sessions of WCCI 2020. Authors who submit papers to this
session are invited to mention it in the form during the submission. Submissions to Regular and Special Sessions follow identical format, instructions, deadlines and procedures
of the other papers.
More information can be found at the following links:
Important dates
CfP
WCCI2020-RACITA.pdf
