A Myhill-Nerode Characterization and Active Learning for One-Clock Timed Automata
Kyveli Doveri, Pierre Ganty, B. Srivathsan
TL;DR
This work extends classical Myhill-Nerode theory to one-clock deterministic timed automata ($1$-DTA) by introducing a machine-independent reset function and half-integral words. It proves that $1$-DTA languages are fully determined by their half-integral word set $ ext{HI}(L)$ and the syntactic reset function $oldsymbol{R}^{L}$, enabling a canonical strict $K_L$-acceptor $ ext{A}_{(oldsymbol{R}^{L}, oughly^{L})}$. The authors establish a Myhill-Nerode style characterization and show minimality within the strict-acceptor class, then present Angluin-style $L^*$-type learning algorithms that recover the canonical acceptor using observation tables and controlled reset guessing. This yields a practical framework for learning $1$-DTA languages and highlights a principled way to compare different canonical representations arising from different resets.
Abstract
We present a Myhill-Nerode style characterization for languages recognized by one-clock deterministic timed automata (1-DTA). Although there is only one clock, distinct automata may reset it differently along the same word. This adds a significant challenge in the search for a canonical automaton. Our characterization is based on a new perspective of 1-DTAs in terms of "half-integral" words that they accept, along with the reset information encoded by them. We apply our results to develop L* style algorithms that learn the canonical 1-DTA.
