Learning Alternating Real-Time Automata

Kazuki Kinoshita; Masaki Waga

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arXiv · 2606.19822

Learning Alternating Real-Time Automata

Kazuki Kinoshita·Masaki Waga

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Abstract

We present the AL*RTA algorithm for learning alternating real-time automata (ARTAs) using membership and equivalence queries. AL*RTA combines ideas from AL*for learning alternating finite automata and NL*RTA for learning nondeterministic real-time automata. We first define ARTAs and show that alternation improves succinctness, although it does not increase expressive power. We then present AL*RTA and show its termination. Our empirical evaluation suggests that AL*RTA generally learns smaller automata than NL*RTA at the cost of more queries.

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Kazuki Kinoshita, Masaki Waga. 2026-06-18. Learning Alternating Real-Time Automata. https://arxiv.org/abs/2606.19822

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