An Approach for Dynamic Split Strategies in Constraint Solving

摘要

In constraint programming, a priori choices statically determine strategies that are crucial for resolution performances. However, the effect of strategies is generally unpredictable. We propose to dynamically change strategies showing bad performances. When this is not enough to improve resolution, we introduce some meta-backtracks. Our goal is to get good performances without the know-how of experts. Some first experimental results show the effectiveness of our approach.