Handling preferences in constraint logic programming with relational optimization

Abstract

In many Constraint Logic Programming (CLP) applications one needs to express not only strict requirements but also preferences. Constraint hierarchies are one way of describing preferred criteria in the statement of a problem. In [18] CLP was extended to integrate constraint hierarchies resulting in Hierarchical Constraint Logic Programming (HCLP). We propose an alternative approach for describing preferred criteria in CLP as a problem of relational optimization (RO). In this approach the programmer defines a preference relation which indicates when a solution is better than another solution. We study several schemes based on pruning for optimizing an objective function, and we show how these schemes can be generalized to handle preference relations defined by CLP programs, while preserving a straightforward logical semantics. Further we show on some examples that the greater flexibility of the relational optimization scheme is not at the cost of efficiency.