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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorvan Oosten, J.
dc.contributor.advisorIemhoff, R.
dc.contributor.authorDulek, Y.M.
dc.date.accessioned2013-08-02T17:01:12Z
dc.date.available2013-08-02
dc.date.available2013-08-02T17:01:12Z
dc.date.issued2013
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/13691
dc.description.abstractThis thesis provides insight into the field of recursion theory, and more specifically, algorithmic learning theory (Gold, 1967). Gold has constructed an abstract model for language acquisition by (Turing) machines. In 2013, Beros has investigated the complexity of the class of languages learnable under Gold's model in terms of the arithmetical hierarchy, as well as the complexity of the classes of languages learnable under certain variations on that model. Beros' proofs are reconstructed and sometimes slightly corrected in this thesis. Furthermore, Beros' claim of the relation between the complexity of a class and the sophistication of the associated learning model is disputed.
dc.description.sponsorshipUtrecht University
dc.format.extent793186 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleLearning paradigms classified by the arithmetical complexity of their learnable language families
dc.type.contentBachelor Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordstheoretical computer science
dc.subject.keywordsrecursion theory
dc.subject.keywordslearning theory
dc.subject.keywordsalgorithmic learning theory
dc.subject.keywordsarithmetical hierarchy
dc.subject.keywordsclassification
dc.subject.keywordscompleteness
dc.subject.keywordsTuring machine
dc.subject.keywordslanguage acquisition
dc.subject.keywordsexplanatory learning
dc.subject.keywordsfinite learning
dc.subject.keywordsbehaviorally correct learning
dc.subject.keywordsanomalous learning
dc.subject.keywordslearning in the limit
dc.subject.keywordsdecision problem
dc.subject.keywordsm-reducibility
dc.subject.courseuuKunstmatige Intelligentie


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