Print Email Facebook Twitter Incrementally Solving STNs by Enforcing Partial Path Consistency Title Incrementally Solving STNs by Enforcing Partial Path Consistency Author Planken, L.R. De Weerdt, M.M. Yorke-Smith, N. Faculty Electrical Engineering, Mathematics and Computer Science Department Software Computer Technology Date 2010-05-12 Abstract Efficient management and propagation of temporal constraints is important for temporal planning as well as for scheduling. During plan development, new events and temporal constraints are added and existing constraints may be tightened; the consistency of the whole temporal network is frequently checked; and results of constraint propagation guide further search. Recent work shows that enforcing partial path consistency provides an efficient means of propagating temporal information for the popular Simple Temporal Network (STN). We show that partial path consistency can be enforced incrementally, thus exploiting the similarities of the constraint network between subsequent edge tightenings. We prove that the worst-case time complexity of our algorithm can be bounded both by the number of edges in the chordal graph (which is better than the previous bound of the number of vertices squared), and by the degree of the chordal graph times the number of vertices incident on updated edges. We show that for many sparse graphs, the latter bound is better than that of the previously best-known approaches. In addition, our algorithm requires space only linear in the number of edges of the chordal graph, whereas earlier work uses space quadratic in the number of vertices. Finally, empirical results show that when incrementally solving sparse STNs, stemming from problems such as Hierarchical Task Network planning, our approach outperforms extant algorithms. To reference this document use: http://resolver.tudelft.nl/uuid:3ca1a60e-8de4-4207-93aa-27e1442ecc18 Publisher Association for the Advancement of Artificial Intelligence (AAAI) Access restriction Campus only Source ICAPS 2010: Proceedings of the 20th International Conference on Automated Planning and Scheduling, Toronto, Canada, 12-16 May 2010 Part of collection Institutional Repository Document type conference paper Rights (c) 2010 Advancement of Artificial Intelligence (AAAI) Files PDF icaps10-incremental1.pdf 391.78 KB Close viewer /islandora/object/uuid:3ca1a60e-8de4-4207-93aa-27e1442ecc18/datastream/OBJ/view