Abstract
We introduce constraint relationships as a means to define qualitative preferences on the constraints of soft constraint problems. The approach is aimed at constraint satisfaction problems (CSPs) with a high number of constraints that make exact preference quantizations hard to maintain manually or hard to anticipate—especially if constraints or preferences change at runtime or are extracted from natural language text. Modelers express preferences over the satisfaction of constraints with a clear semantics regarding preferred tuples without assigning priorities to concrete domain values. We show how a CSP including a set of constraint relationships can linearly be transformed into a k-weighted CSP as a representative of c-semirings that is solved by widely available constraint solvers and compare it with existing techniques. We demonstrate the approach by using a typical example of a dynamic and interactive scheduling problem in AI.
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Acknowledgments
This work has been partially funded by the German Research Foundation (DFG) in the research unit FOR 1085 “OC Trust–Trustworthy Organic Computing Systems”. We would like to thank María Victoria Cengarle for fruitful discussions and the anonymous reviewers for the constructive feedback that led to an improvement of the manuscript.
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Schiendorfer, A., Steghöfer, JP., Knapp, A., Nafz, F., Reif, W. (2013). Constraint Relationships for Soft Constraints. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXX. SGAI 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02621-3_17
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DOI: https://doi.org/10.1007/978-3-319-02621-3_17
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