Patrick Pratt

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This paper investigates a gradual on-line learning algorithm for Harmonic Grammar. By adapting existing convergence proofs for perceptrons, we show that for any nonvarying target language, Harmonic-Grammar learners are guaranteed to converge to an appropriate grammar, if they receive complete information about the structure of the learning data. We also(More)
This paper introduces serial Harmonic Grammar, a version of Optimality Theory (OT; Prince and Smolensky 1993/2004) that reverses two of Prince and Smolensky's basic architectural decisions. 1 One is their choice of constraint ranking over the numerically weighted constraints of its predecessor, Harmonic Grammar (HG; Legendre, Miyata and Smolensky 1990; see(More)
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