Introduction to the special issue on CSP technologies in artificial intelligence

Abstract

Although constraint programming has evolved as an independent domain of research per se, it remains at the same time one of the most fertile and successful areas of artificial intelligence (A.I.). This special issue is intended to illustrate various current topics and research trends in constraint programming that pertain to A.I. It gathers a series of research contributions that range from the study of tractable classes of non-binary CSPs, to efficient algorithms for the extraction of minimal unsatisfiable subsets in constraint networks, and include the application of constraint programming for deciding the robustness of wireless sensor networks and interval methods for numerical constraint programming. The papers in this issue are all revised and expanded research contributions based on results that were presented at the SAT and CSP technologies track at IEEE ICTAI 2013. They were selected as the papers with the highest review scores amongst the 47 full papers submitted to the track, after all the papers submitted to the track had been thoroughly reviewed by at least three reviewers. The authors of the selected papers in the track were invited to submit substantially expanded and revised contributions for this issue. Each of these expanded contributions underwent two additional reviews. We gratefully acknowledge the reviewers for providing deep insights and useful suggestions that helped improve the papers. Finally, we would like to thank Gilles Pesant and Michela Milano, Editors in chief of Constraints, for inviting us to edit this special issue and for their expert help at the different stages of the process.