The Complexity of Learning Linear Temporal Formulas from Examples
Formal Languages and Automata Theory
2021-02-02 v1 Machine Learning
Logic in Computer Science
Abstract
In this paper we initiate the study of the computational complexity of learning linear temporal logic (LTL) formulas from examples. We construct approximation algorithms for fragments of LTL and prove hardness results; in particular we obtain tight bounds for approximation of the fragment containing only the next operator and conjunctions, and prove NP-completeness results for many fragments.
Cite
@article{arxiv.2102.00876,
title = {The Complexity of Learning Linear Temporal Formulas from Examples},
author = {Nathanaël Fijalkow and Guillaume Lagarde},
journal= {arXiv preprint arXiv:2102.00876},
year = {2021}
}