This book introduces a theory, Naive Semantics (NS), a theory of the knowledge underlying natural language understanding. The basic assumption of NS is that knowing what a word means is not very different from knowing anything else, so that there is no difference in form of cognitive representation between lexical semantics and ency clopedic knowledge. NS represents word meanings as commonsense knowledge, and builds no special representation language (other than elements of first-order logic). The idea of teaching computers common sense knowledge originated with McCarthy and Hayes (1969), and has been extended by a number of researchers (Hobbs and Moore, 1985, Lenat et aI, 1986). Commonsense knowledge is a set of naive beliefs, at times vague and inaccurate, about the way the world is structured. Traditionally, word meanings have been viewed as criterial, as giving truth conditions for membership in the classes words name. The theory of NS, in identifying word meanings with commonsense knowledge, sees word meanings as typical descriptions of classes of objects, rather than as criterial descriptions. Therefore, reasoning with NS represen tations is probabilistic rather than monotonic. This book is divided into two parts. Part I elaborates the theory of Naive Semantics. Chapter 1 illustrates and justifies the theory. Chapter 2 details the representation of nouns in the theory, and Chapter 4 the verbs, originally published as "Commonsense Reasoning with Verbs" (McDowell and Dahlgren, 1987). Chapter 3 describes kind types, which are naive constraints on noun representations.

"The idea that prompted the conferenee for which many of these papers were written, and that inspired this book, is stated in the Editorial Introduction reprinted below from Volume 21 of Synthese. The present volume contains the artieles in Synthese 21, Numbers 3-4 and Synthese 22, Numbers 1-2. In addition, it ineludes new papers by Saul Kripke, James McCawley, John R. Ross, and Paul Ziff, and reprints 'Grammar and Philosophy' by P. F. Strawson. Strawson's artiele first appeared in the Proceedings of the Aristotelian Society, Volume 70, and is reprinted with the kind permission of the author and the Aristotelian Society. We also repeat our thanks to the Olivetti Companyand Edizione di Comunita of Milan for permission to inelude the paper by Dana Scott; it also appeared in Synthese 21. DONALO DAVIDSON GILBERT HARMAN EDITORIAL INTRODUCTION The success of linguistics in treating naturallanguages as formal syntactic systems has aroused the interest of a number of linguists in a paralleI or related development of semantics. For the most part quite independ ently, many philosophers and logicians have reeently been applying formai semantic methods to structures increasingly like naturallanguages. While differenees in training, method and vocabulary tend to veil the fact, philosophers and linguists are converging, it seerns, on a common set of interrelated probiems. Sinee philosophers and linguists are working on the same, or very similar, probiems, it would obviously be instructive to compare notes." --

First published in 1989. This Program discusses The Eleventh Annual Conference of the Cognitive Science Society, August 1989 in Ann Arbor, Michigan. The book begins with 66 paper presentations and concludes with 59 poster presentations across over 1000 pages. This program also includes a comprehensive author listing with affiliations and titles.

This open access book introduces Vector semantics, which links the formal theory of word vectors to the cognitive theory of linguistics. The computational linguists and deep learning researchers who developed word vectors have relied primarily on the ever-increasing availability of large corpora and of computers with highly parallel GPU and TPU compute engines, and their focus is with endowing computers with natural language capabilities for practical applications such as machine translation or question answering. Cognitive linguists investigate natural language from the perspective of human cognition, the relation between language and thought, and questions about conceptual universals, relying primarily on in-depth investigation of language in use. In spite of the fact that these two schools both have ‘linguistics’ in their name, so far there has been very limited communication between them, as their historical origins, data collection methods, and conceptual apparatuses are quite different. Vector semantics bridges the gap by presenting a formal theory, cast in terms of linear polytopes, that generalizes both word vectors and conceptual structures, by treating each dictionary definition as an equation, and the entire lexicon as a set of equations mutually constraining all meanings.