Learning Weighted Automata over Principal Ideal Domains

In this paper, we study active learning algorithms for weighted automata over a semiring. We show that a variant of Angluin’s seminal [Formula: see text] algorithm works when the semiring is a principal ideal domain, but not for general semirings such as the natural numbers.

Detalles Bibliográficos
Autores principales: van Heerdt, Gerco, Kupke, Clemens, Rot, Jurriaan, Silva, Alexandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788606/
http://dx.doi.org/10.1007/978-3-030-45231-5_31
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author van Heerdt, Gerco
Kupke, Clemens
Rot, Jurriaan
Silva, Alexandra
author_facet van Heerdt, Gerco
Kupke, Clemens
Rot, Jurriaan
Silva, Alexandra
author_sort van Heerdt, Gerco
collection PubMed
description In this paper, we study active learning algorithms for weighted automata over a semiring. We show that a variant of Angluin’s seminal [Formula: see text] algorithm works when the semiring is a principal ideal domain, but not for general semirings such as the natural numbers.
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spelling pubmed-77886062021-01-07 Learning Weighted Automata over Principal Ideal Domains van Heerdt, Gerco Kupke, Clemens Rot, Jurriaan Silva, Alexandra Foundations of Software Science and Computation Structures Article In this paper, we study active learning algorithms for weighted automata over a semiring. We show that a variant of Angluin’s seminal [Formula: see text] algorithm works when the semiring is a principal ideal domain, but not for general semirings such as the natural numbers. 2020-04-17 /pmc/articles/PMC7788606/ http://dx.doi.org/10.1007/978-3-030-45231-5_31 Text en © The Author(s) 2020 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
spellingShingle Article
van Heerdt, Gerco
Kupke, Clemens
Rot, Jurriaan
Silva, Alexandra
Learning Weighted Automata over Principal Ideal Domains
title Learning Weighted Automata over Principal Ideal Domains
title_full Learning Weighted Automata over Principal Ideal Domains
title_fullStr Learning Weighted Automata over Principal Ideal Domains
title_full_unstemmed Learning Weighted Automata over Principal Ideal Domains
title_short Learning Weighted Automata over Principal Ideal Domains
title_sort learning weighted automata over principal ideal domains
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788606/
http://dx.doi.org/10.1007/978-3-030-45231-5_31
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