We report six experiments on learnability of four non-adjacent phonotactic constraints which differ in their attested frequency and phonetic conditioning factors; liquid harmony, liquid disharmony, backness harmony, and backness disharmony. Our results suggest that such phonotactic constraints can be implicitly learned from brief experience and that learnability of a phonological grammar may be...

A new proof of a result due to Vapnik is given. Its implications for the theory of PAC learnability are discussed, with particular reference to the learnability of functions taking values in a countable set. An application to the theory of artificial neural networks is then given.

The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property o...

Stability is a general notion that quantifies the sensitivity of a learning algorithm’s output to small change in the training dataset (e.g. deletion or replacement of a single training sample). Such conditions have recently been shown to be more powerful to characterize learnability in the general learning setting under i.i.d. samples where uniform convergence is not necessary for learnability...

Within the metaphor of the “mind as a computation device” that dominates cognitive science, understanding human cognition means understanding learnability – not only what (and how) the brain learns, but also what data is available to it from the world. Ideal learnability arguments seek to characterize what knowledge is in theory possible for an ideal reasoner to acquire, which illuminates the p...