Abstract

In this paper we discuss how the ability of the constraint solvers to deal with constraint minimization can be lifted up to various forms of goal optimization within CLP languages. We emphasis the link there is between optimization and negation both in the declarative semantics and in the operational aspects. We also discuss the design of incremental execution models in an "optimization as interaction" paradigm. 1 Introduction Constraint logic programming and concurrent constraint programming are simple and powerful models of computation that have been implemented in several systems over the last decade, and proved successful in a variety of applications ranging from combinatorial optimization problems to complex system modeling [13]. In particular the CLP approach is increasingly used to solve hard scheduling and planning problems [2] [22]. Of course in these applications the ability of the system to generate not all solutions but only best solutions is a fundamental property. ...

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