Q+F
Learning Alternating Real-Time Automata
Kazuki Kinoshita, Masaki Waga
in Room Bin session Q+F Session 3 - Learning and Quantum Systems
(on,
Wed, 16:30, 2 talks over 60 min)
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.