For, more than two decades, Artificial Intelligence developed in relative isolation from “traditional informatics”. Thus, a distinct reservoir of specifically theoretical underlying principles, methods and means were created for it. At present, a process of fusing and of integration between these two domains is under way. Linked to this process is a marked broadening and deepening of the scientific fundamentals and the efficiency potential of modern information technologies. Yet, the potential for increased efficiency is far from being exhausted, particularly with regard to application. Written from the point of view of a computer scientist, this article analyses the practical problems and the obstacles which have appeared during the process of transition to the level of knowledge processing. The procedures which have been devised in order to overcome the problems in question are aimed not only at increasing the quality of knowledge representation and knowledge administration but also at introducing artificial intelligence into traditional application areas. The consistent pursuit of these aims will lead to the integration of artificial intelligence and informatics, so as to produce a homogeneous, scientific discipline. Integration of this sort, however, cannot be accomplished by the simple addition of new components or by placing the two domains side by side. Rather, informatics as a discipline must be restructured and the contents of its separate domains unified. The integration process has been particularly noticeable in the domain of data bank technology, especially with regard to knowledge representation and knowledge bank administration. This process has led to a qualitatively more advanced development stage as compared t o traditional data bank technology and knowledge administration. It is reflected in higher education in the transition from the traditional qualifications of knowledge engineers to those of data bank and knowledge processing engineers.
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