An Experimental Study of Reasoning with Sequences of Point Events

Interval and point algebras are two influential frameworks to model an interval and point based temporal entities. However, in many real world situations we often encounter recurring events that include multiple points, multiple intervals or combinations of points and intervals. Recently, point-based frameworks (MPE [9] and GMPE [10]) for representing and reasoning with sequences of point events have been proposed. These frameworks include new algorithms for solving reasoning tasks with an improved complexity. However, no empirical investigation has been made yet. This paper presents an experimental study of these two frameworks. In this study, we present the design of experiments, implementation of the algorithms, and an empirical performance analysis. Our results indicate that the MPE and GMPE frameworks are not only expressively richer, but also perform better than the traditional approaches to temporal reasoning.