This book provides a broad overview of parameter-setting theory in first and second language acquisition and refines the theory by revisiting and challenging the traditional assumptions that underlie it, based on cross-linguistic language data that cover a range of syntactic and phonological phenomena. From an historical perspective on parameter-setting theory to an introduction to its role in computational linguistics, neurolinguistics, and language change, the reader will find a critique of the most commonly made arguments, as well as an index of all the syntactic, phonological, lexical, and morphological parameters presented in the literature to date. A closer look at the theory itself addresses the following questions: What does a parameter-setting approach to language acquisition entail? What are the underpinnings of the theory? What issues and problems remain to be solved? The empirical studies carried out to test the null subject parameter and verb movement parameter are reviewed to re-examine long-standing theoretical assumptions as well as the learnability implications for first and second language acquisition.

In May 1985 the University of Massachusetts held the first conference on the parameter setting model of grammar and acquisition. The conference was conceived in the belief that there is a new possibility of tightly connecting grammatical studies and language acquisition studies, and that this new possibility has grown out of the new generation of ideas about the relation of Universal Grammar to the grammar of particular languages. The papers in this volume are all concerned in one way or another with the 'parametric' model of grammar, and with its role in explaining the acquisition of language. Before summarizing the accompanying papers, I would like to sketch the intellectual background of these new ideas. It has long been the acknowledged goal of grammatical theorists to explicate the relation between the experience of the child and the knowledge of the adult. Somehow, the child selects a unique grammar (by assumption) compatible with a random partially unreliable sample of some language. In the earliest work in generative grammar, starting with Chomsky's Aspects, and extending to such works as Jackendoffs Lexicalist Syntax (1977), the model of this account was the formal evaluation metric, accompanied by a general rule writing system. The model of acquisition was the following: the child composed a grammar by writing rules in the rule writing system, under the constraint that the rules must be compatible with the data, and that the grammar must be the one most highly valued by the evaluation metric.

One of the main difficulties of applying an evolutionary algorithm (or, as a matter of fact, any heuristic method) to a given problem is to decide on an appropriate set of parameter values. Typically these are specified before the algorithm is run and include population size, selection rate, operator probabilities, not to mention the representation and the operators themselves. This book gives the reader a solid perspective on the different approaches that have been proposed to automate control of these parameters as well as understanding their interactions. The book covers a broad area of evolutionary computation, including genetic algorithms, evolution strategies, genetic programming, estimation of distribution algorithms, and also discusses the issues of specific parameters used in parallel implementations, multi-objective evolutionary algorithms, and practical consideration for real-world applications. It is a recommended read for researchers and practitioners of evolutionary computation and heuristic methods.

Comes with a CD-ROM packed with a variety of problem-solving projects.

Dynamical Grammar explores the consequences for language acquisition, language evolution, and linguistic theory of taking the underlying architecture of the language faculty to be that of a complex adaptive dynamical system. It contains the first results of a new and complex model of language acquisition which the authors have developed to measure how far language input is reflected in language output and thereby get a better idea of just how far the human language faculty is hard-wired.

A great deal has been written on how children learn to speak, but development of language comprehension has been a relatively neglected topic. This book is unique in integrating research in language acquisition, psycholinguistics and neuropsychology to give a comprehensive picture of the process we call "comprehension", right from the reception of an acoustic stimulus at the ear, up to the point where we interpret the message the speaker intended to convey by the utterance. A major theme of the book is that "comprehension" is not a unitary skill: to understand spoken language, one needs the ability to classify incoming speech sounds, to relate them to a "mental lexicon", to interpret the propositions encoded by word order and grammatical inflections, and to use information from the environmental and social context to select, from a wide range of possible interpretations, the one that was intended by the speaker. Furthermore, although neuropsychological and experimental research on adult comprehension can provide useful concepts and methods for assessing comprehension, they should be applied with caution, because a sequential, bottom-up information processing model of comprehension is ill-suited to the developmental context. The emphasis of the book is on children with specific language impairments, but normal development is also given extensive coverage. The focus is on research and theory, rather than practical matters of assessment and intervention. Nevertheless, while this book is not intended as a clinical guide to assessment, it does aim to provide a theoretical framework that can help clinicians develop a clearer understanding of what comprehension involves, and how different types of difficulty may be pinpointed.

In contrast to the prevailing tradition in epistemology, the focus in this book is on low-level inferences, i.e., those inferences that we are usually not consciously aware of and that we share with the cat nearby which infers that the bird which she sees picking grains from the dirt, is able to fly. Presumably, such inferences are not generated by explicit logical reasoning, but logical methods can be used to describe and analyze such inferences. Part 1 gives a purely system-theoretic explication of belief and inference. Part 2 adds a reliabilist theory of justification for inference, with a qualitative notion of reliability being employed. Part 3 recalls and extends various systems of deductive and nonmonotonic logic and thereby explains the semantics of absolute and high reliability. In Part 4 it is proven that qualitative neural networks are able to draw justified deductive and nonmonotonic inferences on the basis of distributed representations. This is derived from a soundness/completeness theorem with regard to cognitive semantics of nonmonotonic reasoning. The appendix extends the theory both logically and ontologically, and relates it to A. Goldman's reliability account of justified belief.