Vertex incremental path consistency for qualitative constraint networks

Abstract

The Interval Algebra (IA) and a subset of the Region Connection Calculus, namely, RCC-8, are the dominant Artificial Intelligence approaches for representing and reasoning about qualitative temporal and topological relations respectively. Such qualitative information can be formulated as a Qualitative Constraint Network (QCN). In this framework, one of the main tasks is to compute the path consistency of a given QCN. We propose a new algorithm that applies path consistency in a vertex incremental manner. Our algorithm enforces path consistency on an initial path consistent QCN augmented by a new temporal or spatial entity and a new set of constraints, and achieves better performance than the state-of-the-art approach. We evaluate our algorithm experimentally with QCNs of RCC-8 and show the efficiency of our approach. © 2014 Springer International Publishing.