Heuristics for Dynamically Adapting Propagation

Building adaptive constraint solvers is a major challenge in constraint programming. An important line of research towards this goal is concerned with ways to dynamically adapt the level of local consistency applied during search. A related problem that is receiving a lot of attention is the design of adaptive branching heuristics. The recently proposed adaptive variable ordering heuristics of Boussemart et al. use information derived from domain wipeouts to identify highly active constraints and focus search on hard parts of the problem resulting in important saves in search effort. In this paper we show how information about domain wipeouts and value deletions gathered during search can be exploited, not only to perform variable selection, but also to dynamically adapt the level of constraint propagation achieved on the constraints of the problem. First we demonstrate that when an adaptive heuristic is used, value deletions and domain wipeouts caused by individual constraints largel...

• Type: Conference
• Year: 2008
• Where: ECAI
• Authors: Kostas Stergiou
• Keywords: Adaptive, Adaptive Constraint Solvers, Artificial Intelligence, Domain Wipeouts, ECAI 2008