Learning from a substructural perspective

Authors:
Pieter Adriaans;Erik de Haas
Affiliations:
Syllogic, Amersfoort, The Netherlands;University of Amsterdam, Amsterdam, The Netherlands
Venue:
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Year:
2000

Citing 3
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A theory of the learnable

Communications of the ACM
Linear logic

Theoretical Computer Science
UML distilled: applying the standard object modeling language

UML distilled: applying the standard object modeling language

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Abstract

In this paper we study learning from a logical perspective. We show that there is a strong relationship between a learning strategy, its formal learning framework and its logical representational theory. This relationship enables one to translate learnability results from one theory to another. Moreover if we go from a classical logic theory to a substructural logic theory, we can transform learnability results of logical concepts to results for string languages. In this paper we will demonstrate such a translation by transforming the Valiant learnability result for boolean concepts to a learnability result for a class of string pattern languages.