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The First International Conference on Information Processing and the Management of Uncertainty (IPMU) was held in 1986 at a time of great debate about the necessity of modelling uncertainty in intelligent systems (which at that time largely meant rule-based expert systems) and the best way of doing so. Whereas the founders of the Conference on Uncertainty in Artificial Intelligence (UAI) in the United States set out with the aim of promoting the use of probability, the organisers of IPMU chose a diametrically opposed course. Though there were a few papers on probability at IPMU '86, the main focus was on alternative methods, primarily those based upon fuzzy sets. Though subsequent conferences have seen greater mix of papers, IPMU remains largely non-probabilistic with the result that the bulk of the participants come from Europe rather than the United States (despite the large amount of work on uncertainty, and especially probability, that is carried out in the US) making IPMU something of a counterpoint to UAT. The difference in participation is exacerbated by the location—whilst the UAI remains in North America, IPMU alternates between Paris and other cities in Europe, including Urbino in 1988 and Palma in 1992.
The paper I wrote for the Knowledge Engineering Review was intended primarily to give a balanced review of different techniques developed in (or imported into) Artificial Intelligence to deal with uncertain knowledge.
This paper reviews many of the very varied concepts of uncertainty used in AI. Because of their great popularity and generality “parallel certainty inference” techniques, so-called, are prominently in the foreground. We illustrate and comment in detail on three of these techniques; Bayes' theory (section 2); Dempster-Shafer theory (section 3); Cohen's model of endorsements (section 4), and give an account of the debate that has arisen around each of them. Techniques of a different kind (such as Zadeh's fuzzy-sets, fuzzy-logic theory, and the use of non-standard logics and methods that manage uncertainty without explicitly dealing with it) may be seen in the background (section 5).
The discussion of technicalities is accompanied by a historical and philosophical excursion on the nature and the use of uncertainty (section 1), and by a brief discussion of the problem of choosing an adequate AI approach to the treatment of uncertainty (section 6). The aim of the paper is to highlight the complex nature of uncertainty and to argue for an open-minded attitude towards its representation and use. In this spirit the pros and cons of uncertainty treatment techniques are presented in order to reflect the various uncertainty types. A guide to the literature in the field, and an extensive bibliography are appended.
In October 1995, Takeshi Furuhashi and his collegues at the Bio-Electronics Laboratory of Nagoya University, Japan, organized the first of a series of on-line workshops, held entirely on the World Wide Web. The advertised advantages of the on-line format were to allow fruitful exchanges while avoiding physical travel, and to guarantee wide visibility of the discussion. The first two workshops in the series were devoted to evolutionary computation; they can be accessed on the web at http://www.bioele.nuee.nagoya-u.ac.jp. The third workshop, named “First On-Line Workshop on Soft Computing” (WSC1), had a broader scope, including all the techniques that go under the heading of “soft computing”, like fuzzy logic, neuro computing, genetic computing, and so on. WSC1 took place from August 19 to 30 1996, and it is accessible on the web at http://www.bioele.nuee.nagoya-u.ac.jp/wsc1/. Because the declared goal of an on-line workshop is to prompt discussion, the rules for submission were looser than in most traditional workshops: papers were not subject to peer review, and it was possible to submit already published papers. All the submitted papers were made visible on the web one week before the workshop, and people could send comments and questions by email during the two workshop weeks; all the questions, comments, and authors' replies are also visible at the WSC1 web site.
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