Computational Intelligence

The field of Computational Intelligence (CI) covers all sorts of techniques for subsymbolic (numerical) knowledge processing, such as the well known Fuzzy Logic (FL), Neural Networks (NN), Genetic Programming (GP), and Evolutionary Strategies (ES), as well as other approaches with lesser dissemination. Computational intelligence techniques are generally bottom-up, where order and structure emerges from an unstructured beginning.

Computational Intelligence, also known as Soft Computing, differs from Operations Research: The two areas are connected by the problem domains they are applied in, but while Operations Research algorithms usually come with crisp (and strict) conditions on the scope of applicability and proven guarantees for a solution (or even an optimal solution), Soft Computing puts no conditions on the problem but also provides no guarantees for success. This deficiency is compensated by the robustness of these methods.

DORTMUND INTELLIGENCE PROJECT achieves results by applying an inductive learning process, which was designed to address all potential weaknesses and to combine the strengths of the methods of Hard Computing and Soft Computing. The implementation of the process forms a powerful hybrid engine, that can be used to solve a broad range of problems in different business areas: A context free self-learning machine waiting for your task.