Point-based approaches to qualitative temporal reasoning

Abstract

We address the general problem of finding algorithms for efficient, qualitative, point-based temporal reasoning over a set of operations. We consider general reasoners tailored for temporal domains that exhibit a particular structure and introduce such a reasoner based on the series-parallel graph reasoner of Delgrande and Gupta; this reasoner is also an extension of the TimeGraph reasoner 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 performs better for query answering.

Propagating temporal relations of intervals by matrix

“…For instance, abstract model temporal logics like Templog (Abadi and Manna 1989) is based on linear and branching time temporal logics and temporal logic programming languages (Tang 1989); rei® ed temporal logics like the token rei® cation temporal logic (Halpern and Sholam 1991;Vila and Reichgelt 1996), temporal extensions and implementations (Hrycej 1993;Tang 1989;Yampratoom and Allen 1993), and more general works on temporal logic (Barringer, Kuiper, and Pnueli 1984;Staab and Hahn 1999). Certainly, there are also a number of researches on time, such as adding synchronization constraints between concurrent agents such that their concurrent execution satis® es a given temporal property (Shoham and Tennenholtz 1994;Stuart 1985), and a method for synchronizing multiagent plans from goals described by a temporal logic (Kabanza 1995), natural language understanding (Allen 1984), general planning (Allen and Koomen 1983;Haddawy 1996;Pirri and Reiter 1995), and binary constraint problems (Ladkin and Maddux 1994;Meiri 1996;Mouhoub, Charpillet, and Haton 1998;Nebel and Buckert 1995;Nebel 1997;Schwalb, Kask, and Dechter 1994;Schwalb and Dechter 1997;Schwalb 1997;Tolba, Charpillet, and Haton 1991;Vila andReichgelt 1996, Vilain andKautz 1986). Much of the work on temporal reasoning in Arti® cial Intelligence are summarized in Vila (1944) .…”