The Selection of Syntactic Knowledge

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Abstract
Most recent approaches to language learnability and acquisition have assumed that parameter setting is largely a deductive process. This article develops the thesis that parameter setting is correctly viewed as nondeductive. In particular, deductive approaches can be computationally costly and, in the worst case, are equal in cost to a brute enumerative search through the hypothesis space. The approach developed here uses natural selection, as simulated by a genetic algorithm, to simulate: parameter setting. A method is developed for evaluating the behavior of parsing devices relative to an environment (the input text), translating between parsing devices and a genome (a hypothesis string), and combining hypotheses via mating and mutation. A learner based on such a system will eventually arrive at the grammar for the least language compatible with its environment. We discuss three basic learnability properties that must characterize the learner's linguistic environment. Finally, we develop some recommenda...

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