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2021 | OriginalPaper | Chapter

Learnability and Positive Equivalence Relations

Authors : David Belanger, Ziyuan Gao, Sanjay Jain, Wei Li, Frank Stephan

Published in: Language and Automata Theory and Applications

Publisher: Springer International Publishing

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Abstract

Prior work of Gavryushkin, Khoussainov, Jain and Stephan investigated what algebraic structures can be realised in worlds given by a positive (= recursively enumerable) equivalence relation which partitions the natural numbers into infinitely many equivalence classes. The present work investigates the infinite one-one numbered recursively enumerable (r.e.) families realised by such relations and asks how the choice of the equivalence relation impacts the learnability properties of these classes when studying learnability in the limit from positive examples, also known as learning from text. For all choices of such positive equivalence relations, for each of the following entries, there are one-one numbered r.e. families which satisfy it: (a) they are behaviourally correctly learnable but not vacillatorily learnable; (b) they are explanatorily learnable but not confidently learnable; (c) they are not behaviourally correctly learnable. Furthermore, there is a positive equivalence relation which enforces that (d) every vacillatorily learnable one-one numbered family of languages closed under this equivalence relation is already explanatorily learnable and cannot be confidently learnable.

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Footnotes
1
The reader is referred to [19, 28] for an introduction to other basic learning notions in inductive inference and to [14, 69, 12, 14, 15, 18, 2123] for further reading
 
2
However, there are many natural families of languages that are learnable in the limit, such as the class of non-erasing pattern languages (see [1, Example 1]).
 
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Metadata
Title
Learnability and Positive Equivalence Relations
Authors
David Belanger
Ziyuan Gao
Sanjay Jain
Wei Li
Frank Stephan
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-68195-1_12

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