Soft Computing is a discipline that deals with the design of hybrid intelligent systems which, in contrast to classical hard computing techniques, are tolerant to imprecision, uncertainty, partial truth, and approximation. Thus tractable, robust, and low cost solutions to real-world problems are achieved. The main constituents of Soft Computing are fuzzy logic, neural networks, evolutionary computation, and probabilistic reasoning.

Since the term Soft Computing was coined at the beginning of the 90s, this area has experienced a rapid development of its fundamentals as well as its applications. The summer course reviews the fundamentals of this discipline, describes many real-world applications, and, in particular, treats new trends and future directions of the field. Participants will gain insight into the potential of soft computing techniques and the state of the art in the area. To achieve this, the lecturers have been selected from the leaders of the different branches of Soft Computing.

The summer course is supported by the "Future Directions in Fuzzy Sets and Systems" Task Force, Fuzzy Systems Technical Committee, IEEE Computational Intelligence Society, several members of which participate in the course.