Learning real-time automata

Real-time automata (RTAs) are a subclass of timed automata with only one clock which resets at each transition. In this paper, we present an active learning algorithm for deterministic real-time automata (DRTAs) in both continuous-time semantics and discrete-time semantics. For a target language recognized by a DRTA A\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal{A}$$\end{document}, we convert the problem of learning DRTA A\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal{A}$$\end{document} to the problem of learning a canonical real-time automaton A\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathbb{A}$$\end{document} with the same recognized language, i.e., L(A)=L(A)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal{L}(\mathbb{A})=\mathcal{L}(\mathcal{A})$$\end{document}. The algorithm is inspired by existing learning algorithms for symbolic automata.