Dynamic CSPs for Interval-Based Temporal Reasoning

Abstract

Many applications such as planning, scheduling, computational linguistics and computational models for molecular biology involve systems capable of managing qualitative and metric time information. An important issue in designing such systems is the efficient handling of temporal information in an evolutive environment. In a previous work, we have developed a temporal model, TemPro, based on the interval algebra, to express such information in terms of qualitative and quantitative temporal constraints. In order to find a good policy for solving time constraints in a dynamic environment, we present in this paper, a study of dynamic arc-consistency algorithms in the case of temporal constraints. We show that, an adaptation of the new AC-3 algorithm presents promising results comparing to the other dynamic arc-consistency algorithms. Indeed, while keeping an optimal worst-case time complexity, this algorithm has a better space complexity than the other methods.