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Article
Temporal Probabilistic Logic Programs
International Conference on Logic Programming (ICLP’99) Proceedings: Las Cruces, NM
  • Alex Dekhtyar, University of Maryland - College Park
  • Michael I. Dekhtyar, Tver State University
  • V. S. Subrahmanian, University of Maryland - College Park
Publication Date
8-13-1999
Abstract

There are many applications where the precise time at which an event will occur (or has occurred) is uncertain. Temporal probabilistic logic programs (TPLPs) allow a programmer to express knowledge about such events. In this paper, we develop a model theory, fixpoint theory, and proof theory for TPLPs, and show that the fixpoint theory may be used to enumerate consequences of a TPLP in a sound and complete manner. Likewise the proof theory provides a sound and complete inference system. Last, but not least, we provide complexity results for TPLPs, showing in particular, that reasonable classes of TPLPs have polynomial data complexity.

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Citation Information
Alex Dekhtyar, Michael I. Dekhtyar and V. S. Subrahmanian. "Temporal Probabilistic Logic Programs" International Conference on Logic Programming (ICLP’99) Proceedings: Las Cruces, NM (1999) p. 109 - 123
Available at: http://works.bepress.com/dekhtyar/46/