Skip to Main Content
In this work we exploit search process features to dynamically adapt a constraint programming solver in order to more efficiently solve constraint satisfaction problems. The main novelty of our approach is that we reconfigure the searching or search process based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies.
Date of Conference: 4-7 Dec. 2009