A Sound-and-Complete Propagation-Based Algorithm for Checking the Dynamic Consistency of Conditional Simple Temporal Networks

Abstract

A Conditional Simple Temporal Network (CSTN) is a data structure for representing and reasoning about time-points and temporal constraints, some of which may apply only in certain scenarios. The scenarios in a CSTN are represented by conjunctions of propositional literals whose truth values are not known in advance, but instead are observed in real time, during execution. The most important property of a CSTN is whether it is dynamically consistent (DC), that is, whether there exists a strategy for executing its time-points such that all relevant constraints are guaranteed to be satisfied no matter which scenario is incrementally revealed during execution. Prior approaches to determining the dynamic consistency of CSTNs (a.k.a., solving the Conditional Simple Temporal Problem) are primarily of theoretical interest, they have not been realized in practical algorithms. This paper presents a sound-and-complete DC-checking algorithm for CSTNs that is based on the propagation of constraints labeled by propositions. The paper also presents an empirical evaluation of the new algorithm that demonstrates that it may be practical for a variety of applications. This is the first empirical evaluation of any DC-checking algorithm for CSTNs ever reported in the literature.