General algorithms for testing the ambiguity of finite automata

Cyril Allauzen, Mehryar Mohri, Ashish Rastogi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents efficient algorithms for testing the finite, polynomial, and exponential ambiguity of finite automata with ε-transitions. It gives an algorithm for testing the exponential ambiguity of an automaton A in time O(|A|E2, and finite or polynomial ambiguity in time O(|A|E3, where |A| E denotes the number of transitions of A. These complexities significantly improve over the previous best complexities given for the same problem. Furthermore, the algorithms presented are simple and based on a general algorithm for the composition or intersection of automata. We also give an algorithm to determine in time O(|A|E3 the degree of polynomial ambiguity of a polynomially ambiguous automaton A. Finally, we present an application of our algorithms to an approximate computation of the entropy of a probabilistic automaton.

Original languageEnglish (US)
Title of host publicationDevelopments in Language Theory - 12th International Conference, DLT 2008, Proceedings
Pages108-120
Number of pages13
DOIs
StatePublished - Oct 27 2008
Event12th International Conference on Developments in Language Theory, DLT 2008 - Kyoto, Japan
Duration: Sep 16 2008Sep 19 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5257 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Developments in Language Theory, DLT 2008
CountryJapan
CityKyoto
Period9/16/089/19/08

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Allauzen, C., Mohri, M., & Rastogi, A. (2008). General algorithms for testing the ambiguity of finite automata. In Developments in Language Theory - 12th International Conference, DLT 2008, Proceedings (pp. 108-120). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5257 LNCS). https://doi.org/10.1007/978-3-540-85780-8_8