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Answer Set Programming for Regular Inference
2020
Applied Sciences
We propose an approach to non-deterministic finite automaton (NFA) inductive synthesis that is based on answer set programming (ASP) solvers. To that end, we explain how an NFA and its response to input samples can be encoded as rules in a logic program. We then ask an ASP solver to find an answer set for the program, which we use to extract the automaton of the required size. We conduct a series of experiments on some benchmark sets, using the implementation of our approach. The results show
doi:10.3390/app10217700
fatcat:2ppdhlkpq5fvjguneovofzogze