Allen's Interval Algebra Makes the Difference
This work addresses temporal reasoning challenges in applications like planning and scheduling, but it is incremental as it builds on existing ASP and constraint methods.
The paper tackles the problem of encoding Allen's Interval Algebra for temporal reasoning by proposing a novel encoding using answer-set programming extended with difference constraints (ASP(DL)), and demonstrates its performance through a preliminary experimental evaluation.
Allen's Interval Algebra constitutes a framework for reasoning about temporal information in a qualitative manner. In particular, it uses intervals, i.e., pairs of endpoints, on the timeline to represent entities corresponding to actions, events, or tasks, and binary relations such as precedes and overlaps to encode the possible configurations between those entities. Allen's calculus has found its way in many academic and industrial applications that involve, most commonly, planning and scheduling, temporal databases, and healthcare. In this paper, we present a novel encoding of Interval Algebra using answer-set programming (ASP) extended by difference constraints, i.e., the fragment abbreviated as ASP(DL), and demonstrate its performance via a preliminary experimental evaluation. Although our ASP encoding is presented in the case of Allen's calculus for the sake of clarity, we suggest that analogous encodings can be devised for other point-based calculi, too.