This study is aimed at a brief, carefully focused retrospective view at the Computational Intelligence – a paradigm supporting the analysis and synthesis of intelligent systems. We stress the reason behind the emergence of this discipline and identify its main features. We highlight the synergistic aspects of Computational Intelligence arising from an interaction and collaboration of fuzzy sets, neural networks, and evolutionary optimization. Some promising directions of future fundamental and applied research are also identified.
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
