منابع مشابه
Non U-Shaped Vacillatory and Team Learning
U-shaped learning behaviour in cognitive development involves learning, unlearning and relearning. It occurs, for example, in learning irregular verbs. The prior cognitive science literature is occupied with how humans do it, for example, general rules versus tables of exceptions. This paper is mostly concerned with whether Ushaped learning behaviour may be necessary in the abstract mathematica...
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In learning, a semantic or behavioral U-shape occurs when a learner rst learns, then unlearns, and, nally, relearns, some target concept (on the way to success). Within the framework of Inductive Inference, previous results have shown, for example, that such Ushapes are unnecessary for explanatory learning, but are necessary for behaviorally correct and non-trivial vacillatory learning. Herein ...
متن کاملMemory-Limited U-Shaped Learning
U-shaped learning is a learning behaviour in which the learner first learns something, then unlearns it and finally relearns it. Such a behaviour, observed by psychologists, for example, in the learning of past-tenses of English verbs, has been widely discussed among psychologists and cognitive scientists as a fundamental example of the non-monotonicity of learning. Previous theory literature h...
متن کاملVariations on U-Shaped Learning
The paper deals with the following problem: is returning to wrong conjectures necessary to achieve full power of algorithmic learning? Returning to wrong conjectures complements the paradigm of U-shaped learning [3,7,9,24,29] when a learner returns to old correct conjectures. We explore our problem for classical models of learning in the limit from positive data: explanatory learning (when a le...
متن کاملAnomalous Vacillatory Learning
In 1986, Osherson, Stob and Weinstein asked whether two variants of anomalous vacillatory learning, TxtFex∗ ∗ and TxtFext∗ ∗ , could be distinguished [3]. In both, a machine is permitted to vacillate between a finite number of hypotheses and to make a finite number of errors. TxtFext∗ ∗ -learning requires that hypotheses output infinitely often must describe the same finite variant of the corre...
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ژورنال
عنوان ژورنال: Journal of Computer and System Sciences
سال: 2008
ISSN: 0022-0000
DOI: 10.1016/j.jcss.2007.06.013