A General Approach for Building Constraint Languages

This paper describes a general approach for the integration of arbitrary declarative languages and constraint systems. The main idea is to consider declarative programs together with the language evaluation mechanisms as constraint solvers and to integrate them into an overall system of cooperating solvers. Exemplarily, we present the integration of a logic language with a constraint system, and the extension of a functional logic language with constraints. The approach allows to build constraint languages according to current requirements and thus it enables comfortable modelling and solving of many problems

Spatial Inference - Learning vs. Constraint Solving

We present a comparison of two new approaches for solving constraints occurring in spatial inference. In contrast to qualitative spatial reasoning we use a metric description, where relations between pairs of objects are represented by parameterized homogenous transformation matrices with numerical (nonlinear) constraints. We employ interval arithmetics based constraint solving and methods of machine learning in combination with a new algorithm for generating depictions for spatial inference

An architecture for the combination of constraint solvers

In tis paper, an architecture for the combination of different constraint solvers with the help or projections is proposed. By means of the definition of an interface and restricting properties of the operations of constraint solvers we are able to define a mechanism for the open and consistent combination of constraint systems. We enable the use of a functional logic language as constraint solver for constraints over functional expressions in the overall system. The syntax of a language which allows the specification of mixed constraints of different constraint domains and its operational semantics are introduced. We compare our approach with BALI, an environment for designing and executing constraint solver combinations. (orig.)Available from TIB Hannover: RR 7739(98-08) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Methoden zur automatischen Parallelisierung (Constraint-) logischer Programme

Available from TIB Hannover: RR 7739(97-08)+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

Integration and Optimization of Rule-based Constraint Solvers

One lesson learned from practical constraint solving applications is that constraints are often heterogeneous. Solving such constraints requires a collaboration of constraint solvers. In this paper, we introduce a methodology for the tight integration of CHR constraint programs into one such program. CHR is a high-level rule-based language for writing constraint solvers and reasoning systems. A constraint solver is well-behaved if it is terminating and conuent. When merging constraint solvers, this property may be lost. Based on previous results on CHR program analysis and transformation we show how to utilize completion to regain well-behavedness. We identify a class of solvers whose union is always confluent and we show that for preserving termination such a class is hard to find. The merged and completed constraint solvers may contain redundant rules. Utilizing the notion of operational equivalence, which is decidable for well-behaved CHR programs, we present a method to detect redundant rules in a CHR program

Constraint-based modeling and scheduling of clinical pathways

In this article a constraint-based modeling of clinical pathways, in particular of surgical pathways, is introduced and used for an optimized scheduling of their tasks. The addressed optimization criteria are based on practical experiences in the area of Constraint Programming applications in medical work flow management. Objective functions having empirical evidence for their adequacy in the considered use cases are formally presented. It is shown how they are respected while scheduling clinical pathways