Cutting Diamonds: Temporal DLs with Probabilistic Distributions over Data

TL;DR

This paper introduces a probabilistic extension of a temporal description logic, integrating probability distributions into ABox assertions to enhance reasoning about temporal data with uncertainty.

Contribution

It adapts probabilistic temporal logic to DL-Lite, enabling probabilistic reasoning over temporal assertions in a well-established description logic framework.

Findings

Analyzes satisfiability over equiparametric geometric distributions.

Extends temporal DLs with probabilistic constructors in ABox assertions.

Provides a foundation for reasoning with temporal and probabilistic data.

Abstract

Recent work has studied a probabilistic extension of the temporal logic LTL that refines the eventuality (or diamond) constructor with a probability distribution on when will this eventuality be satisfied. In this paper, we adapt this notion to a well established temporal extension of DL-Lite, allowing the new probabilistic constructor only in the ABox assertions. We investigate the satisfiability problem of this new temporal DL over equiparametric geometric distributions.