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By Denis Bouyssou, Didier Dubois, Henri Prade, Marc Pirlot

This publication presents an outline of the most equipment and ends up in the formal learn of the human decision-making strategy, as outlined in a comparatively broad feel. A key target of the procedure contained this is to aim to collapse boundaries among quite a few disciplines encompassed through this box, together with psychology, economics and computing device technology. a lot of these methods have contributed to development during this extremely important and much-studied subject some time past, yet none have proved adequate to date to outline a whole realizing of the hugely complicated tactics and results. This ebook offers the reader with state of the art assurance of the sector, primarily forming a roadmap to the sector of determination analysis.

The first a part of the booklet is dedicated to easy suggestions and strategies for representing and fixing choice difficulties, starting from operational learn to synthetic intelligence. Later chapters supply an in depth evaluate of the decision-making strategy lower than stipulations of danger and uncertainty. ultimately, there are chapters overlaying quite a few methods to multi-criteria decision-making. every one bankruptcy is written via specialists within the subject involved, and includes an intensive bibliography for extra interpreting and reference.

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Extra info for Decision Making Process: Concepts and Methods

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For an excellent reference survey, see [EHR 02]. g. VONW 86] or indirectly (through, for instance, the AHP method [SAA 80], the UTA method [JAC 82] or the MACBETH method, [BAN 94]). We find the methods known as ‘outranking methods’ within the second category. This name was given by Bernard Roy [ROY 85] to the preference relation representing the concept ‘at least as good as’. Such methods are based on the principle: when we compare x to y under multiple criteria, x will be at least as good as y if it is the case for a weighted majority of criteria and there are no strong ‘blocking minorities’ [TSO 02b].

Such methods are based on the principle: when we compare x to y under multiple criteria, x will be at least as good as y if it is the case for a weighted majority of criteria and there are no strong ‘blocking minorities’ [TSO 02b]. The reader can obtain more details on these methods in [ROY 91, ROY 96, SCHÄ 85, SCHÄ 96, VIN 92]. Recently, the possibility of constructing such a relation from holistic evaluations of the alternatives provided by the decision maker was shown in [GRE 99, PAW 94]. More generally, the extension of the theory of rough sets through the use of dominance-based decision rules [GRE 01, SLOW 05] allows us to take into account purely ordinal evaluations.

SAB 98, SAB 01, SLOW 90] although it did not solve all conceptual problems related to uncertainty modeling. That said, the reader should remember that since the late 1980s there has been a large discussion on innovating the whole field of decision under uncertainty and risk [COH 80, FAR 05, GIL 89, GIL 93, GIL 02a, GIL 02b, JAF 88, JAF 89, JAF 93, MAC 82, MAC 92, MAC 95, NAU 95, QUI 93, SCHM 89]. The discussion on handling uncertainty is concluded by recalling the contributions based on the use of other logic formalisms that allow the inevitable uncertainties, ambiguities and inconsistencies which characterize a decision-aiding process to be taken into account [FORT 02, PER 98, TSO 95, TSO 02a, TSO 02b].

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