Faster MUSE CSP Arc Consistency Algorithms

Abstract

MUSE CSP (MU ltiply SEgmented C onstraint Satisfaction Problem) (Helzerman & Harper, 1994, 1996) is an extension to the constraint satisfaction problem (CSP) which is especially useful for problems which segment into multiple instances of CSP which share variables. MUSE CSP has been used in such diverse applications as improving the accuracy of spoken language understanding systems (Harper & Helzerman, 1995a) and managing contexts in NLP database query systems (Harper & Helzerman, 1995b). In this paper, we focus on providing faster MUSE arc consistency algorithms by applying techniques similar to those developed by Bessière