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An analysis of finite parameter learning in linguistic spaces

The study of language acquisition involves determining how children learn the linguistic phenomena of their first language. This thesis analyzes the Triggering Learning Algorithm, which describes how children set the parameters which define the linguistic variation seen in the syntax of natural language. This thesis describes enhancements to an implementation of this algorithm and the results found from the implementation. This implementation allows for more careful study of the algorithm and of its known problems. It allows us to examine in more depth the solutions which have been proposed for these problems. The results show that the theory correctly predicts some principles expected to be true of language acquisition. However, many of the proposed principles are shown to make incorrect predictions about the learnability of certain kinds of languages. This thesis discusses a second potential solution and ways in which it can be tested as well as other ways to test the predictions of the theory. Thesis Supervisor: Robert C. Berwick Title: Professor of Computer Science and Engineering