New Research Perspectives in the Emerging Field of Computational Intelligence to Economic Modeling

Computational Intelligence (CI) is a new development paradigm of intelligentsystems which has resulted from a synergy between fuzzy sets, artificial neuralnetworks, evolutionary computation, machine learning, etc., broadeningcomputer science, physics, economics, engineering, mathematics, statistics. It isimperative to know why these tools can be potentially relevant and effective toeconomic and financial modeling. This paper presents, after a synergic newparadigm of intelligent systems, as a practical case study the fuzzy and temporalproperties of knowledge formalism embedded in an Intelligent Control System(ICS), based on FT-algorithm. We are not dealing high with level reasoningmethods, because we think that real-time problems can only be solved by ratherlow-level reasoning. Most of the overall run-time of fuzzy expert systems isused in the match phase. To achieve a fast reasoning the number of fuzzy setoperations must be reduced. For this, we use a fuzzy compiled structure ofknowledge, like Rete, because it is required for real-time responses. Solving thematch-time predictability problem would allow us to built much more powerfulreasoning techniques.