Point-Based Approaches to Qualitative Temporal Reasoning

Weaddress the general problemof finding algorithms for efficient, qualitative, point-basedtemporalreasoning over a set of operations. Weconsider general reasonerstailored for temporaldomainsthat exhibit a particular structure and introduce such a reasoner based on the series-parallel graph reasoner of Delgrandeand Gupta;this reasoner is also an extension of the TimeGraphreasoner of Gerevini and Schubert. Test results indicate that for data with underlying structure, our reasoner performs better than other approaches. When there is no underlying structure in the data, our reasoner still performsbetter for query answering.

• Type: Conference
• Year: 1998
• Where: PRICAI
• Authors: Tim Van Allen, James P. Delgrande, Arvind Gupta
• Keywords: Artificial Intelligence, PRICAI 1998, Problemof Finding Algorithms, Reasoner, Series-parallel Graph Reasoner