Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.tcs.2018.12.022
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dc.titleIntrinsic complexity of partial learning
dc.contributor.authorJAIN, S
dc.contributor.authorKINBER, E
dc.date.accessioned2019-06-07T01:33:52Z
dc.date.available2019-06-07T01:33:52Z
dc.date.issued2019-07-12
dc.identifier.citationJAIN, S, KINBER, E (2019-07-12). Intrinsic complexity of partial learning. Theoretical Computer Science 776 : 43-63. ScholarBank@NUS Repository. https://doi.org/10.1016/j.tcs.2018.12.022
dc.identifier.issn0304-3975
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/155272
dc.description.abstract© 2018 Elsevier B.V. A partial learner in the limit [25], given a representation of the target language (a text), outputs a sequence of conjectures, where one correct conjecture appears infinitely many times and other conjectures each appear a finite number of times. Following [7] and [21], we define intrinsic complexity of partial learning, based on reducibilities between learning problems. Although the whole class of recursively enumerable languages is partially learnable (see [25]) and, thus, belongs to the complete learnability degree, we discovered a rich structure of incomplete degrees, reflecting different types of learning strategies (based, to some extent, on topological structures of the target language classes). We also exhibit examples of complete classes that illuminate the character of the strategies for partial learning of the hardest classes.
dc.publisherElsevier BV
dc.sourceElements
dc.typeArticle
dc.date.updated2019-06-03T09:30:17Z
dc.contributor.departmentDEPARTMENT OF COMPUTER SCIENCE
dc.description.doi10.1016/j.tcs.2018.12.022
dc.description.sourcetitleTheoretical Computer Science
dc.description.volume776
dc.description.page43-63
dc.published.stateAccepted
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