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Outline

Weighted Automata–Theory and Applications

Abstract

We extend the disambiguation construction presented by Mohri and Riley [1] in two ways. First we change the underlying structure of their automata from words to trees and second we show that these results hold not only for the tropical semiring but also the arctic one.

FAQs

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What defines the expressive power of weighted automata compared to neural networks?add

The research indicates that weighted automata have a distinct expressive power; for instance, certain operations on weighted automata were found decidable while equivalent operations in neural networks proved computationally complex, notably in 2020.

How do max-plus semiring concepts influence cost-register automata?add

The study reveals that the max-plus semiring introduces unique computational properties, such as resolving ambiguities in automata structures and defining restrictions leading to recognizable classes of languages, discussed extensively by Laure Daviaud in 2021.

Which recent findings elucidate the universality problem for unambiguous register automata?add

Recent findings show that unambiguous register automata maintain their universality despite complexity challenges, with significant advancements made in decoding their behavior outlined in Karin Quaas's 2021 presentation.

What unique characteristics do weighted context-free grammars exhibit over strong bimonoids?add

Weighted context-free grammars exhibit behaviors defined by two semantics that coincide under right distributive conditions; this distinction aids in identifying language transformations as of 2022.

What does the approximate simulation imply for the state reduction of fuzzy automata?add

The findings indicate that approximate simulations offer superior state reduction capabilities for fuzzy automata compared to exact simulations, which may fail to allow for any reduction at all.

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