Andre Jones – författare

Problems in decision making and in other areas such as pattern recogni­ tion, control, structural engineering etc. involve numerous aspects of uncertainty. Additional vagueness is introduced as models become more complex but not necessarily more meaningful by the added details. During the last two decades one has become more and more aware of the fact that not all this uncertainty is of stochastic (random) cha­ racter and that, therefore, it can not be modelled appropriately by probability theory. This becomes the more obvious the more we want to represent formally human knowledge. As far as uncertain data are concerned, we have neither instru­ ments nor reasoning at our disposal as well defined and unquestionable as those used in the probability theory. This almost infallible do­ main is the result of a tremendous work by the whole scientific world. But when measures are dubious, bad or no longer possible and when we really have to make use of the richness of human reasoning in its variety, then the theories dealing with the treatment of uncertainty, some quite new and other ones older, provide the required complement, and fill in the gap left in the field of knowledge representation. Nowadays, various theories are widely used: fuzzy sets, belief function, the convenient associations between probability and fuzzines~ etc ••• We are more and more in need of a wide range of instruments and theories to build models that are more and more adapted to the most complex systems.

Problems in decision making and in other areas such as pattern recogni­ tion, control, structural engineering etc. involve numerous aspects of uncertainty. Additional vagueness is introduced as models become more complex but not necessarily more meaningful by the added details. During the last two decades one has become more and more aware of the fact that not all this uncertainty is of stochastic (random) cha­ racter and that, therefore, it can not be modelled appropriately by probability theory. This becomes the more obvious the more we want to represent formally human knowledge. As far as uncertain data are concerned, we have neither instru­ ments nor reasoning at our disposal as well defined and unquestionable as those used in the probability theory. This almost infallible do­ main is the result of a tremendous work by the whole scientific world. But when measures are dubious, bad or no longer possible and when we really have to make use of the richness of human reasoning in its variety, then the theories dealing with the treatment of uncertainty, some quite new and other ones older, provide the required complement, and fill in the gap left in the field of knowledge representation. Nowadays, various theories are widely used: fuzzy sets, belief function, the convenient associations between probability and fuzzines~ etc ••• We are more and more in need of a wide range of instruments and theories to build models that are more and more adapted to the most complex systems.

ANDRE JONES As everybody knovs, the computer has been used for over ten years in education. Since the first conference at Irvine "The computer in physics instruction" (1965). various meetings on this subject have been organized in many places, which dealt with very different subjects. Work groups have been set up at international level (by the UNESCO, OECD, ... ) and at national level in various countries. Of the prominent extra-European meetings, we will only keep the most important ones. for example those held in the U.S.A. on the "Computer Use in Undergraduate Curriculum" and in Canada, "The Canadian Symposium on Instructional Technology" (1972). As a matter of fact, there have been quite a lot of conferences on this subject in Europe too. For example, the OECD entrusted us with the organizing of a center called U.C.O. 0.1. which would be aimed at two Objectives. On the one hand, to set up a aata bank on the experiments made in the field of the computer use in education; and on the second hand, to stimulate research in this field.