Efficiently Enforcing Path Consistency on Qualitative Constraint Networks by Use of Abstraction.

Partial closure under weak composition, or partial ⋄-consistency for short, is essential for tackling fundamental reasoning problems associated with qualitative constraint networks, such as the satisfiability checking problem, and therefore it is crucial to be able to enforce it as fast as possible. To this end, we propose a new algorithm, called PWC α , for efficiently enforcing partial ⋄-consistency on qualitative constraint networks, that exploits the notion of abstraction for qualitative constraint networks, utilizes certain properties of partial ⋄-consistency, and adapts the functionalities of some state-of-theart algorithms to its design. It is worth noting that, as opposed to a related approach in the recent literature, algorithm PWC α is complete for arbitrary qualitative constraint networks. The evaluation that we conducted with qualitative constraint networks of the Region Connection Calculus against a competing state-of-the-art generic algorithm for enforcing partial ⋄-consistency, demonstrates the usefulness and efficiency of algorithm PWC α .