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The main idea of this project is to demonstrate a way of programmatically finding the optimal solution to a problem without quantifying it. Whereas most preference engines (such as Netflix, Amazon or Pandora's recommendation systems) tend to use a numerical score assigned to various attributes, this preference engine will rely on a user-defined network of attribute-value preference relationships. The user will enter attributes, the domains of the attributes, the possible alternatives (and their values relative to the attributes' domains), and then arrange their conditions and preferences relative to these attributes by arranging nodes and edges. A simple example would be a system of two attributes where dependability of workers is more important to a manager than communication skills. Using this system, neither needs to be quantified (turned into a number) in order to say that if all else is equal, high dependability is better than high communication. The user of this system can impose as many refinements on the relationships between attributes as they like without having to come up with some arbitrary scoring system. This project is intended to be useful to designers of complex hardware or software systems, public policy decision makers, managers of large institutions, trust negotiation (for web security, etc.) and a wide variety of other applications.
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