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|E 2, and finite or polynomial ambiguity in time O(|A|E 3, 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|E 3 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
Volume5257 LNCS
DOIs
StatePublished - 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)03029743
ISSN (Electronic)16113349

Other

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

Fingerprint

Finite Automata
Finite automata
Testing
Automata
Polynomials
Polynomial
Probabilistic Automata
Ambiguous
Efficient Algorithms
Intersection
Entropy
Ambiguity
Denote
Chemical analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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 (Vol. 5257 LNCS, 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

General algorithms for testing the ambiguity of finite automata. / Allauzen, Cyril; Mohri, Mehryar; Rastogi, Ashish.

Developments in Language Theory - 12th International Conference, DLT 2008, Proceedings. Vol. 5257 LNCS 2008. p. 108-120 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5257 LNCS).

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

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. vol. 5257 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5257 LNCS, pp. 108-120, 12th International Conference on Developments in Language Theory, DLT 2008, Kyoto, Japan, 9/16/08. https://doi.org/10.1007/978-3-540-85780-8_8
Allauzen C, Mohri M, Rastogi A. General algorithms for testing the ambiguity of finite automata. In Developments in Language Theory - 12th International Conference, DLT 2008, Proceedings. Vol. 5257 LNCS. 2008. p. 108-120. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-85780-8_8
Allauzen, Cyril ; Mohri, Mehryar ; Rastogi, Ashish. / General algorithms for testing the ambiguity of finite automata. Developments in Language Theory - 12th International Conference, DLT 2008, Proceedings. Vol. 5257 LNCS 2008. pp. 108-120 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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