New perspectives on Causal Networks: the first CaNew workshop

We are pleased to introduce a selection of the papers presented at the 1998 workshop on `Causal Networks from Inference to Data Mining', CaNew '98, [59]. This workshop was initiated from the feeling, shared by the organizers and co-chairs, that the ®eld of Bayesian and, in general, Causal Networks deserved special attention from the international research community. We had a growing feeling that several areas had been neglected in research or deserved more attention. The common background of the editors and co-chairs being in Machine Learning, we felt that some ideas that had been long been in use in Machine Learning had not been applied to Causal Networks. However, we also felt that other aspects dealing with the knowledge representation aspects of the Causal Network formalism were also of interest, namely, the construction of networks that used di€erent uncertainty formalisms, new inference methods and the relationship between the classical interpretation of Causal Network and the new ones. The rest of the Workshop Programme Committee members had a similar feeling about that and we tried to convey this by introducing in the workshop title both ends of the Causal Networks research spectrum: from inference to Data Mining. We comment in more detail in Section 3 the opportunities that, from our point of view, lay hidden between both. International Journal of Approximate Reasoning 24 (2000) 1±10 www.elsevier.com/locate/ijar