Tomorrow, the international Hybrid Artificial Intelligence Systems conference (HAIS) gets started in Salamanca with the special session of Knowledge Extraction based on Evolutionary Learning (KEEL). In this special session, the following 14 papers that use evolutionary algorithms for different purposes in the field of machine learning will be presented:

1. A hybrid bumble bees mating optimization – GRASP algorithm for clustering by Yannis Marinakis, Magdalene Marinaki, and Nikolaos Matsatsinis
2. A first study on the use of cooperative coevolution for instance and feature selection in classification with nearest neighbour rule by Joaquín Derrac, Salvador García, and Francisco Herrera
3. Unsupervised feature selection in high dimensional spaces and uncertainty by José R. Villar, María R. Suárez, Javier Sedano, and Felipe Mateos
4. Non-dominated multi-objective evolutionary algorithm based on fuzzy rules extraction for subgroup discovery by C. J. Carmona, P. González, M.J. del Jesus, and F. Herrera
5. A first study on the use of interval-valued fuzzy sets with genetic tuning for classification with imbalanced data-sets by J. Sanz, A. Fernández, H. Bustince, and F. Herrera
6. Feature construction and feature selection in presence of attribute interactions by Leila S. Shafti and Eduardo Pérez
7. Multiobjective evolutionary clustering approach to security vulnerability assessments by Guiomar Corral, Àlvaro Garcia-Piquer, Albert Orriols-Puig, Albert Fornells, and Elisabet Golobardes
8. Beyond homemade artificial data sets by Nuria Macià, Albert Orriols-Puig, and Ester Bernadó-Mansilla
9. A three-objective evolutionary approach to generate Mamdani fuzzy rule-based systems by Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, and Francesco Marcelloni
10. A new component selection algorithm based on metrics and fuzzy clustering analysis by Camelia Serban, Andreea Vescan, and Horia F. Pop
11. Multilabel classification with gene expression programming by J. L. Ávila, E. L. Gibaja, and S. Ventura
12. An evolutionary ensemble-based method for rule extraction with distributed data by Diego M. Escalante, Miguel Angel Rodriguez, and Antonio Peregrin
13. Evolutionary extraction of association rules: A preliminary study on their effectiveness by Nicolò Flugy Papè, Jesús Alcalá-Fdez, Andrea Bonarini, and Francisco Herrera
14. A minimum-risk genetic fuzzy classifier based on low quality data by Ana M. Palacios, Luciano Sánchez, and Inés Couso

We’ll have to wait until tomorrow to know more what these promising titles hide.