Commutative regular shuffle closed languages, noetherian property, and learning theory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

To develop computational learning theory of commutative regular shuffle closed languages, we study finite elasticity for classes of (semi)group-like structures. One is the class of ANd + F such that A is a matrix of size e × d with nonnegative integer entries and F consists of at most k number of e-dimensional nonnegative integer vectors, and another is the class Xd k of AZd + F such that A is a square matrix of size d with integer entries and F consists of at most k number of ddimensional integer vectors (F is repeated according to the lattice AZd). Each class turns out to be the elementwise unions of k-copies of a more manageable class. So we formulate "learning time" of a class and then study in general setting how much "learning time" is increased by the elementwise union, by using Ramsey number. We also point out that such a standpoint can be generalized by using Noetherian spaces.

Original languageEnglish
Title of host publicationLanguage and Automata Theory and Applications - Third International Conference, LATA 2009, Proceedings
Pages93-104
Number of pages12
DOIs
Publication statusPublished - 2009
Event3rd International Conference on Language and Automata Theory and Applications, LATA 2009 - Tarragona, Spain
Duration: 2009 Apr 22009 Apr 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5457
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Language and Automata Theory and Applications, LATA 2009
Country/TerritorySpain
CityTarragona
Period09/4/209/4/8

Fingerprint

Dive into the research topics of 'Commutative regular shuffle closed languages, noetherian property, and learning theory'. Together they form a unique fingerprint.

Cite this