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arXiv · 1405.5610

Hyper-Minimization for Deterministic Weighted Tree Automata

Andreas Maletti·Daniel Quernheim
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Abstract

Hyper-minimization is a state reduction technique that allows a finite change in the semantics. The theory for hyper-minimization of deterministic weighted tree automata is provided. The presence of weights slightly complicates the situation in comparison to the unweighted case. In addition, the first hyper-minimization algorithm for deterministic weighted tree automata, weighted over commutative semifields, is provided together with some implementation remarks that enable an efficient implementation. In fact, the same run-time O(m log n) as in the unweighted case is obtained, where m is the size of the deterministic weighted tree automaton and n is its number of states.

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Andreas Maletti, Daniel Quernheim. 2014-05-22. Hyper-Minimization for Deterministic Weighted Tree Automata. https://doi.org/10.4204/eptcs.151.22

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