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UMINF 16.18

Minimization of finite state automata through partition aggregation

We present a minimization algorithm for finite state automata that finds and merges bisimulation-equivalent states, identified through partition aggregation. We show the algorithm to be correct and have a time complexity of a low polynomial. The algorithm is slower than those based on partition refinement, but has the advantage that intermediate solutions are also language equivalent to $\machine$. As a result, the algorithm can be run as a maintenance task in the background, and put on hold when needed. Furthermore, the algorithm essentially searches for the maximal model of a characteristic formula for the input automaton, so many of the optimisation techniques used to gain efficiency in SAT solvers are likely to apply.


Automata minimization, Bisimulation, Finite state automata, Propositional logic


Johanna Bjorklund and Loek Cleophas

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Entry responsible: Johanna Bjorklund

Page Responsible: Frank Drewes