| Resumen |
Computational intelligence is branch of artificial intelligence that studies a wide range of tasks and problems especially difficult for traditional algorithms to deal with: those problems that include uncertainty, highly stochastic behavior, or fuzziness. Probably the majority of problems currently dealt with within the artificial intelligence framework, and a large share of problems addressed by modern computer science in general, fall in this category. Computational intelligence seeks to achieve solutions of such complex problems with the techniques that presumably human brain uses, and with the degree of quality equal, or superior, to the quality with which humans solve such problems. Among the problems particularly difficult for computers and particularly easy for human brain we can mention everyday human activities such as intuition, learning, noticing patterns, dealing with language, vision, and spatial orientation. Their computer counterparts are the areas of machine learning, natural language processing, and image processing, among others. Of these areas, machine learning is a set of techniques deeply penetrating all other areas of artificial intelligence, while natural language processing, image processing and computer vision, and other research areas have more applied character and are oriented to model different specific abilities of the human brain. For this special issue, we have selected a representative collection of fourteen papers presenting the latest advances in all these areas of research and practical applications. |
