By F. Krückeberg (auth.), Professor Dr. Heinz Schwärtzel, Professor Dr. Igor A. Mizin (eds.)
During the previous couple of years, desktops have advanced from natural quantity crunching machines to "intelligent" challenge fixing instruments. expanding attempt has been spent at the research of recent techniques and the applying of ideas to genuine international difficulties. during this method, intriguing new thoughts have developed delivering help for progressively more technical and cost-effective facets. purposes diversity from the layout and improvement of extremely hugely built-in circuits to fully new man-machine interfaces, from software program engineering instruments to fault analysis structures, from selection help to even the research of unemployment. Following a primary joint workshop on complicated details Processing held in July 1988 on the Institute for difficulties of Informatics of the USSR Academy of Sciences (IPIAN) at Moscow, this was once the second one time that scientists and researchers from the USSR Academy of Sciences and Siemens AG, company learn and improvement, exchanged effects and mentioned fresh advances within the box of utilized desktop sciences. Initiated by way of Prof. Dr. I. Mizin, Corresponding Member of the USSR Academy of Sciences and Director of IPIAN, and Prof. Dr. H. Schwartzel, vp of the Siemens AG and Head of the utilized computing device technological know-how & software program division, a joint symposium used to be prepared on the USSR Academy of Sciences in Moscow on June fifth and sixth 1990. The conferences on details Processing and software program and structures layout Automation supplied a foundation either for displays of ongoing learn and for discussions approximately particular problems.
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Extra resources for Advanced Information Processing: Proceedings of a Joint Symposium. Information Processing and Software Systems Design Automation. Academy of Sciences of the USSR, Siemens AG, FRG Moscow, June 5/6, 1990
Although there are various different ways of characterizing and defining individual learning, there is common agreement that neuronal activity is fundamental to this type of learning (Barnes, 1986). g. (Hinton, 1987; Holland, 1975; Weiss, 1989; Machine Learning, 1988) for an overview). Our current work concentrates on the combination of these two types of learning (Weiss, 1990). Thereby we are primarily interested in the possibilities and limits of hybrid learning systems resulting from such a combination.
In Proceedings of the First Conference on Theoretical Aspects of Knowledge Representation, Toronto. de Kleer, J. (1986). An assumption based truth maintenance system. Artificial Intelligence, 28:127-162. Dorigo, M. and Schatz, B. (1990). A parallel neural network simulator. To appear in: FKI-Reihe, Institut fUr Informatik, Technische Universitat Miinchen. , and Freksa, C. (1984). Towards a theory of knowledge representation systems. In Bibel, W. , editors, Artificial Intelligence Methodology, Systems, Applications.
There are several types of knowledge representation in a logical production with a computer, semantic net & frame models being the most often used of them. A logical representation is the most general one, which is capable to reflect all aspects of the outer world. It is based on the predicate calculation. Moreover, such well known specialists in the AI as N. Nilson consider the net & frame representation as an actual way of predicate calculation. It is the most developed and strict formalism, when we are interested in the representation of the most general laws.