The goal of the research project ParXCel (Machine Learning and Parallelization for Scalable Constraint Solving) is to develop machine learning and parallelization technologies that (1) systematically support personalized constraint solving including corresponding conflict detection and diagnosis and (2) exploit parallelization concepts to boost the performance or reasoning algorithms. In this context, the technical objectives of ParXCel are the following:

1. Integration of machine learning concepts into constraint-based reasoning to allow personalization for configuration.
2. To develop parallelization approaches that help to boost the performance of constraint solving and related analysis tasks.