Hard and soft constraints for reasoning about qualitative conditional preferences
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Many real life optimization problems are defined in terms of both hard and soft constraints, and qualitative conditional preferences. However, there is as yet no single framework for combined reasoning about these three kinds of information. In this paper we study how to exploit classical and soft constraint solvers for handling qualitative preference statements such as those captured by the CP-nets model. In particular, we show how hard constraints are sufficient to model the optimal outcomes of a possibly cyclic CP-net, and how soft constraints can faithfully approximate the semantics of acyclic conditional preference statements whilst improving the computational efficiency of reasoning about these statements.
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- Hard and soft constraints for reasoning about qualitative conditional preferences
Journal of Heuristics
Volume 12, Issue 4-5 , pp 263-285
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- Kluwer Academic Publishers
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- Hard and Soft Constraints
- Author Affiliations
- 1. William Davidson Faculty of Industrial Engineering and Management, Technion—Israel Institute of Technology, Technion City, Haifa, Israel
- 2. Department of Computer Science, University College Cork, Cork, Ireland
- 3. Department of Mathematics, University of Padova, Padova, Italy
- 4. National ICT Australia and School of Computer Science and Engineering, University of New South Wales, Sydney, Australia