Bipolar Preference Problems: Framework, Properties and Solving Techniques. Pini, M., S., Rossi, F., Venable, K., B., & Bistarelli, S. In Proceedings of the 2006 ERCIM Workshop on Constraints, Springer LNAI 4561, pages 78-92, 2007. Springer.
Website abstract bibtex Real-life problems present several kinds of preferences. We focus\non problems with both positive and negative preferences, that we\ncall bipolar preference problems. Although seemingly specular notions,\nthese two kinds of preferences should be dealt with differently to\nobtain the desired natural behaviour. We technically address this\nby generalizing the soft constraint formalism, which is able to model\nproblems with one kind of preferences. We show that soft constraints\nmodel only negative preferences, and we define a new mathematical\nstructure which allows to handle positive preferences as well. We\nalso address the issue of the compensation between positive and negative\npreferences, studying the properties of this operation. Finally,\nwe extend the notion of arc consistency to bipolar problems, and\nwe show how branch and bound (with or without constraint propagation)\ncan be easily adapted to solve such problems.
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abstract = {Real-life problems present several kinds of preferences. We focus\non problems with both positive and negative preferences, that we\ncall bipolar preference problems. Although seemingly specular notions,\nthese two kinds of preferences should be dealt with differently to\nobtain the desired natural behaviour. We technically address this\nby generalizing the soft constraint formalism, which is able to model\nproblems with one kind of preferences. We show that soft constraints\nmodel only negative preferences, and we define a new mathematical\nstructure which allows to handle positive preferences as well. We\nalso address the issue of the compensation between positive and negative\npreferences, studying the properties of this operation. Finally,\nwe extend the notion of arc consistency to bipolar problems, and\nwe show how branch and bound (with or without constraint propagation)\ncan be easily adapted to solve such problems.},
bibtype = {inProceedings},
author = {Pini, Maria Silvia and Rossi, Francesca and Venable, Kristen Brent and Bistarelli, Stefano},
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