Computational Preference Assessment and Optimization for Group Decision Support

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The abundance of data and range of options afforded by advances in information technology have profoundly changed the nature of the decisions that face individuals, professionals and policy makers. Intelligent decision support systems (DSSs) are vital to help manage this complexity. Unfortunately, DSSs require considerable knowledge of (individual or organizational) preferences, leading to the "preference bottleneck": how do we elicit preferences in a natural, unobtrusive manner? In group decision making (or social choice) problems, the preference bottleneck is exacerbated, since a DSS must aggregate the preferences of individual group members. This not only increases the volume of preference information needed, but it provides incentives for individuals to misrepresent their preferences to the detriment of the social objective.