Concepts of a learning object-oriented problem solver (LOOPS) This presentation discusses concepts of a learning object-oriented problem solver (LOOPS) which is on the one hand a new and general framework for a decision support system (DSS) and on the other hand answers some open or partially neglected questions in multiple criteria decision making (MCDM). These are, for instance: How should implicit knowledge about `good alternatives’ be processed? What method should be used? How should its parameters be adjusted?par The main methodological goals of LOOPS are 1) learning and 2) the integration of methods. These concepts are discussed and ways of their realization are suggested: Integration is achieved by providing several methods, by utilizing neural networks, and by developing a concept of generalized networks. Learning is realized by evolutionary algorithms. Essential to the implementation of these concepts within LOOPS is the object-oriented paradigm which is also discussed.
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References in zbMATH (referenced in 5 articles )
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