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Learning Languages from Positive Data and a Finite Number of Queries

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Book cover FSTTCS 2004: Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3328))

Abstract

A computational model for learning languages in the limit from full positive data and a bounded number of queries to the teacher (oracle) is introduced and explored. Equivalence, superset, and subset queries are considered. If the answer is negative, the teacher may provide a counterexample. We consider several types of counterexamples: arbitrary, least counterexamples, and no counterexamples. A number of hierarchies based on the number of queries (answers) and types of answers/ counterexamples is established. Capabilities of learning with different types of queries are compared. In most cases, one or two queries of one type can sometimes do more than any bounded number of queries of another type. Still, surprisingly, a finite number of subset queries is sufficient to simulate the same number of equivalence queries when behaviourally correct  learners do not receive counterexamples and may have unbounded number of errors in almost all conjectures.

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Jain, S., Kinber, E. (2004). Learning Languages from Positive Data and a Finite Number of Queries. In: Lodaya, K., Mahajan, M. (eds) FSTTCS 2004: Foundations of Software Technology and Theoretical Computer Science. FSTTCS 2004. Lecture Notes in Computer Science, vol 3328. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30538-5_30

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  • DOI: https://doi.org/10.1007/978-3-540-30538-5_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24058-7

  • Online ISBN: 978-3-540-30538-5

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