Unrestricted nogood recording in CSP search

Abstract

Recently spectacular improvements in the performance of SAT solvers have been achieved through nogood recording (clause learning). In the CSP literature, on the other hand, nogood recording remains a fairly minor technique for improving backtracking algorithms. In this paper we demonstrate how recent nogood recording techniques from SAT can be generalized to CSPs. The result is a significant enhancement over current nogood recording techniques used in CSPs. We also report on some preliminary empirical results which indicate that generalized nogood recording can have a significant performance benefit. © Springer-Verlag 2003.