Temporal Reasoning Based on Semi-Intervals (Revised Version)

A generalization of Allen's interval-based approach to temporal reasoning is presented. The scope of reasoning capabilities can be considerably extended by using relations between semi-intervals rather than intervals as the basic units of knowledge. Semi-intervals correspond to beginnings or endings of temporal events. We develop a representational framework in which relations between semi-intervals appear as coarse knowledge in comparison with relations between intervals. We demonstrate the advantages of reasoning on the basis of semi-intervals: 1) coarse knowledge can be processed directly; computational effort is saved; 2) incomplete knowledge about temporal intervals can be fully exploited; 3) incomplete inferences made on the basis of complete knowledge can be used directly for further inference steps; 4) there is no trade-off in computational strength for the added flexibility and efficiency; 5) semi-intervals correspond to natural entities both from a cognitive and from a computational point of view. The presented scheme supports reasoning on the basis of fine-grained or complete knowledge, on the basis of coarse or incomplete knowledge, and on combinations of both kinds of knowledge. The notion of `conceptual neighborhood' is central to the presented approach. Besides enhancing the reasoning capabilities in several directions, this notion allows for a drastic compaction of the knowledge base underlying Allen's inference scheme. A connection to fuzzy reasoning on the basis of `conceptual neighborhood' is drawn. It is suggested that reasoning based on the simplified knowledge base may be particularly suited for the implementation of parallel inference engines. [Revised version was published as: Freksa C, Temporal reasoning based on semi-intervals, Artificial Intelligence 54 (1992) 199-227.]

ICSI Technical Report TR-90-016

Technical Report