AI Magazine Volume 7 Number 1 (1986) ( AAAI) of the crucial terms involved in his analysis, such as "probability" Mauadne 4(4):7-14 falsity of his claims is often impossible to assess. Nute, Donald k. '(1980) Topics in conditional logic Dordrecht, Holland: conceptions upon which his view is based do indeed conform M. Ringle, (Ed.), Philosophical Perspectives in Artificial Intelligence traditional conceptions should not be taken for granted, Terry L. Rankin his observation that "Probability theory is today our primary At hens, Georgia such as "average" and "likely," and therefore it is the most natural language for describing those aspects of (heuristic) performance that we seek to improve" (p. Artificial Intelligence and Robotics: On general theoretical grounds, I think, there are excellent Five Overviews. Busi-reasons to suppose that (a)-(f) are fundamental ness/Technology Books; 1984. Gevarter's work was published by the National that serious difficulties seem to confront the theoretical Bureau of Standards as a set of five volumes, and this book, framework he apparently endorses, where these difficulties published by Business/Technology Books, is Gevarter's are especially severe from an epistemological perspective.

John Haugeland's discussion is generally very clear, concrete, accurate, and interesting. My main regret is that he does not take the space to more fully explore certain ideas.

In fact, such a pattern can itself be considered a frame, where the position of each pixel is a slot, and the shade or A recent article by Ronald Brachman (Brachman, color at each pixel is then the attached value. It should 1985) points out some philosophical or semantic problems then be possible to represent this pattern as I have just in using the notion of a prototype, which is described by described it-z.e., by a frame representing the background, using default properties. The problem arises since default partially obscured or covered by a frame representing the properties can be overridden or cancelled in representing object of interest, partially obscured or covered by some particular instances, and therefore lack definitional power: other objects. The fact that some part of the object of interest is obscured does not mean that it is no longer there, nor As an example, Brachman presents an elephant joke: that it is not intrinsic to the object's definition. Q: What's big and gray, has a trunk, and lives in the trees?

The Advanced Computational Methods Center (ACMC) established at the University of Georgia in 1984, supports several research projects in artificial intelligence. The primary goal of AI research at ACMC is the design and installation of a logic-programming environment with advanced natural language processing and knowledge-acquisition capabilities on the university's highly parallel CYBERPLUS system from Control Data Corporation. This article briefly describes current research projects in artificial intelligence at ACMC

The third edition of this best-selling guide to Prolog and Artificial Intelligence has been updated to include key developments in the field while retaining its lucid approach to these topics. Divided into two parts, the first part of the book introduces the programming language Prolog, while the second part teaches Artificial Intelligence using Prolog as a tool for the implementation of AI techniques. Prolog has its roots in logic, however the main aim of this book is to teach Prolog as a practical programming tool. This text therefore concentrates on the art of using the basic mechanisms of Prolog to solve interesting problems. The third edition has been fully revised and extended to provide an even greater range of applications, which further enhance its value as a self-contained guide to Prolog, AI or AI Programming for students and professional programmers alike.

This book is a new addition to the Harper & Row Computer Science and Technology Series, and is intended for senior undergraduates or first-year graduate students. It is an introduction to mathematical logic, with some computer science applications. The first chapter sets the goals for the book, which include explanations of proof theory, model theory, and automatic theorem providing for those formulas that are true. The second chapter is designed as an introduction for the novice to those mathematical concepts used throughout the rest of the book. The author says, "This fairly lengthy chapter has been included in order to make this book as self-contained as possible. Readers with a firm mathematical background may skim or even skip this chapter entirely."

The technology for building knowledge-based systems by inductive inference from examples hasbeen demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directionsMachine Learning, 1, p. 81-106

A variety of proposals for preferred methodological approaches has been advanced in the recent artificial intelligence (AI) literature. The article presents a review of such perspectives discussed in the existing literature and then considers a descriptive and relatively specific typology of these differing research perspectives. It is argued that researchers should make their methodological orientations explicit when communicating research results, to increase both the quality of research reports and their comprehensibility for other participants in the field. For a reader of the AI literature, an understanding of the various methodological perspectives will be of immediate benefit, giving a framework for understanding and evaluating research reports.

Further, new application domains such as computer -aided design (CAD), computer- aided manufacturing (CAM), and image understanding based on formal logic require novel concepts in knowledge representation and inference beyond the capabilities of current production rule systems. Fundamental research in artificial intelligence is concentrated at Corporate Research and Development (CR&D), with advanced development and applications pursued in parallel efforts by operating departments. The fundamental research and advanced applications activities are strongly coupled, providing research teams with opportunities for field evaluations of new concepts and systems. This article summarizes current research projects at CR&D and gives an overview of applications within the company.