A Conditional Simple Temporal Network with Uncertainty and Decisions (CSTNUD) is a formalism for temporal plans that models controllable and uncontrollable durations as well as controllable and uncontrollable choices simultaneously. In the classic top-down model-based engineering approach, a designer builds CSTNUDs to model, validate and execute some temporal plans of interest. In this paper, we investigate a bottom-up approach by providing a deterministic polynomial time algorithm to mine a CSTNUD from a set of execution traces (i.e., a log). We provide a prototype implementation and we test it with a set of artificial data. Finally, we elaborate on consistency and controllability of mined networks.
|Titolo:||Mining CSTNUDs significant for a set of traces is polynomial|
Zavatteri, Matteo (Corresponding)
|Data di pubblicazione:||2021|
|Appare nelle tipologie:||01.01 Articolo in Rivista|