John McCarthy's influence in computer science ranges from the invention of LISP and time-sharing to the coining of the term AI and the founding of the AI laboratory at Stanford University. One of the foremost figures in computer sciences, McCarthy has written papers which are widely referenced and stand as milestones of development over a wide range of topics. In this collection of reviews, McCarthy staunchly defends the importance of Artificial Intelligence research against its attackers; this book gathers McCarthy's reviews of books which discuss and criticise the future of AI. Here, McCarthy explores the larger questions associated with AI, such as the question of the nature of intelligence, of the acquisition and application of knowledge, and the question of the politics behind this research.

Early formal specifications of natural language syntax were quite closely connected to the notion of abstract machines for computing them. This provided a very natural means of gauging the relative difficulty of processing various constructions, as well as offering some insight into the abstract properties of the human language faculty. More recently, this approach has been superseded by one in which languages are specified in terms of systems of constraints on the structure of their sentences. This has made complexity results difficult to obtain. This book introduces a way of obtaining such results. It presents a natural and quite general means of expressing constraints on the structure of trees and shows that the languages that can be specified by systems of such constraints are exactly those computable by a particular standard class of abstract machines. Thus the difficulty of processing a construction can be reduced to the difficulty of expressing the constraints that specify it. The technique is demonstrated by applying it to a fairly complete treatment of English within the framework of Government and Binding theory, with the result of showing that its complexity is much less than has heretofore been assumed.

This volume is a compilation of revised versions of papers presented at a conference held in spring 1994 at the Centre for Interdisciplinary Research (ZiF) in Bielefeld, Germany.

Presented in this book is a theory of concept formation and understanding that does not make use of a notion of an innate mental language as a means of concept representation. Instead, experimental concepts are treated semantically as stabilising structuring of growing sets of data, which are sets of experienced satisfaction situations for expressions, and theoretical concepts are based on coherent sets of general sentences held true. There are two kinds of structures to be established: general concepts by means of similarity sets under perspectives and historical concepts. This gives rise to a theory of understanding new situations and expressions by integrating new data into established sets of data salva stability, or by extending the conceptual structure in a metaphorical or metonymical way. The theory provides a way to understand what identity between propositional attitudes amounts to, especially how people can have more or less the same belief.

Dynamic Syntax is a formal model of utterance description that attempts to articulate and substantiate the claim that human linguistic knowledge is essentially the ability to process language in context. The model provides an explicit demonstration of how interpretation is built up incrementally from the information provided by the words as they are encountered. Drawing from a range of analyses of natural language data, the authors use formal definitions, step-by-step derivations, and detailed lexical definitions to illustrate this new form of syntactic analysis and to show how the model can be applied to a broad range of constructions and languages.