“Lazy Model Expansion: Interleaving Grounding with Search” by Broes De Cat, Marc Denecker, Maurice Bruynooghe and Peter Stuckey Finding satisfying assignments for the variables involved in a set of constraints can be cast as a (bounded) model generation problem: search for (bounded) models of a theory in some logic. The state-of-the-art approach for bounded model generation for rich knowledge representation languages is ground-and-solve: reduce the theory to a ground or propositional one and apply a search algorithm to the resulting theory.An important bottleneck is the blow-up of the size of the theory caused by the grounding phase. Lazily grounding the theory during search is a way to overcome this bottleneck. We present a theoretical framework and an implementation in the context of the FO(.) knowledge representation language. Instead of grounding all parts of a theory, justifications are derived for some parts of it…