2009/03/18

ACM news

New System for Improving Decision Support Systems
Universidad Politecnica de Madrid (03/13/09) 

Universidad Politecnica de Madrid School of Computing researchers have developed a system designed to improve decision-making processes in complex situations. The system was tested on the restoration of Lake Svyatoye in Belarus, which was contaminated by the Chernobyl accident. Professors Antonio Jimenez, Alfonso Mateos, and Sixto Rios, from the Department of Artificial Intelligence's Decision Analysis and Statistics Group, aimed to account for incomplete information and any possible effects those gaps could have on decision making. Multi-Attribute Utility Theory is often used to solve decision-making problems. The theory says that after building a hierarchy of objectives and identifying a set of alternatives and each alternative's value for impact on the objectives, the decision maker's preferences are quantified. The new system uses two approaches to manage incomplete information, which occurs when the impacts of some alternatives and attributes are unknown. The first approach redistributes criteria weights with missing values or impacts throughout the objectives hierarchy and across other criteria, which means the criteria hierarchy and its assigned weights vary when each alternative is analyzed depending on the criteria with missing values. The second approach associates the citerion range, the set of possible values, as the impact for a criterion with missing values, which means the entire range of values are considered possible and equally likely.

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