Computational Complexity and Natural Language (Computational Models of Cognition and Perception)

Computational Complexity and Natural Language heralds an entirely new way of looking at grammatical systems. It applies the recently developed computer science tool of complexity theory to the study of natural language. A unified and coherent account emerges of how complexity theory can probe the information-processing structure of grammars, discovering why a grammar is easy or difficult to process and suggesting where to look for additional grammatical constraints. For the linguist or cognitive scientist, the book presents a nontechnical introduction to complexity theory and discusses its strengths, its weaknesses, and how it can be used to study grammars. For the computer scientist, it offers a more sophisticated and efficient computational analysis of linguistic theories. Given the variety of new techniques rising from complexity theory, the authors foresee a developing cooperation among linguists, cognitive scientists, and computer scientists toward understanding the nature of human language. The book also describes a set of case studies that use complexity theory to analyze grammatical problems. And it examines several grammatical systems currently of interest to computational linguists - including spelling-change/dictionary lookup and morphological analysis, agreement processes in natural language, and lexical-functional grammar - demonstrating how complexity analysis can illuminate and improve each one.

A Bradford Book.

Staff at the MIT Artificial Intelligence Laboratory.

Robert C. Berwick is Professor of Computational Linguistics and Computer Science and Engineering, in the Laboratory for Information and Decision Systems and the Institute for Data, Systems, and Society at MIT and the author of Computational Complexity and Natural Language and The Acquisition of Syntactic Knowledge, both published by the MIT Press.