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Deciding where the truth lies between these two extremes is the main purpose of John Haugeland's marvelously lucid and witty book on what artificial intelligence is all about. Although presented entirely in non-technical terms, it neither oversimplifies the science nor evades the fundamental philosophical issues. Far from ducking the really hard questions, it takes them on, one by one. Artificial intelligence, Haugeland notes, is based on a very good idea, which might well be right, and just as well might not. That idea, the idea that human thinking and machine computing are "radically the same," provides the central theme for his illuminating and provocative book about this exciting new field.

Gives a complete account of the mathematical structure, statistical analysis, and applications of finite mixture distributions. Direct applications include economics, medicine, remote sensing, sedimentology, and signal detection (pattern recognition). Also describes indirect applications--in outlier models, density estimation, Bayesian and empirical Bayes analysis, and robustness studies. Goes on to cover mathematical concepts such as identifiability and information, and the inferential problems associated with data from a mixture. Approximate sequential methods are developed here, in order to deal with estimation difficulties and engineering applications.

Berkeley, Calif: University of California Press

The area of database query evaluation is relatively well understood, as is shown by a recent survey article [1]. The two basic strategies are bottom-up, which creates intermediate relations (using, e.g., sort-merge joining), and top-down, which avoids intermediate relations by means of indexing and relation scanning. These two approaches each have relative advantages, and are intermixed in many standard implementations. The same principles apply to recursive queries, but their interaction is much less understood; in fact, lately there has been heated debate between adherents of PROLOG (top-down) and Deductive Databases (bottom-up). The present paper is the first serious attempt at merging these techniques.

Programs that make decisions need mechanisms for representing and reasoning about the desirability of the possible consequences of their choices. This work is an exploration of preference models based on utility theory. The framework presented is distinguished by a qualitative view of preferences and a knowledge-based approach to the application of utility theory. The design for a comprehensive preference modeler is implemented in part by the U tility R easoning P ackage (URP), a collection of facilities for constructing and analyzing preference models. Qualitative mathematical reasoning techniques are employed to develop partial specifications of single-attribute utility functions from qualitative preference assertions.

Backtrack search is often used to solve constraint satisfaction problems. A relationship involving the structure of the constraints is described that provides a bound on the backtracking required to advance deeper into the backtrack tree. This analysis leads to upper bounds on the effort required for solution of a class of constraint satisfaction problems. The solutions involve a combination of relaxation preprocessing and backtrack search. The bounds are expressed in terms of the structure of the constraint connections.

MODIFIED PAPER TITLE AND ABSTRACT DUE TO SLIGHTLY MODIFIED SCOPE: TITLE: Nonlinear Force Profile Used to Increase the Performance of a Haptic User Interface for Teleoperating a Robotic Hand Natural movements and force feedback are important elements in using teleoperated equipment if complex and speedy manipulation tasks are to be accomplished in hazardous environments, such as hot cells, glove boxes, decommissioning, explosives disarmament, and space. The research associated with this paper hypothesizes that a user interface and complementary radiation compatible robotic hand that integrates the human hand's anthropometric properties, speed capability, nonlinear strength profile, reduction of active degrees of freedommore » during the transition from manipulation to grasping, and just noticeable difference force sensation characteristics will enhance a user's teleoperation performance. The main contribution of this research is in that a system that concisely integrates all these factors has yet to be developed and furthermore has yet to be applied to a hazardous environment as those referenced above. In fact, the most prominent slave manipulator teleoperation technology in use today is based on a design patented in 1945 (Patent 2632574) [1]. The robotic hand/user interface systems of similar function as the one being developed in this research limit their design input requirements in the best case to only complementing the hand's anthropometric properties, speed capability, and linearly scaled force application relationship (e.g.

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

Search algorithms for finding optimal solutions are, at least from the practical point of view, often enough intractible, so that the search for good ('satisficing') solutions becomes a research topic of its own interest. Satisficing solutions and different approaches to obtain them under various criteria is the subject of these notes, published in the series "Research notes in artificial intelligence". In an introductory chapter the author presents the known point - value and the point - { { set of values} } identification used in search- based decision-algorithms for guiding the search and discusses some of their advantages and disadvantages. This motivates the here studied alternative approach using that evaluation functions do not return a point - value or a range of values corresponding to a point (state) in a tree but now a distribution function, that describes the possible location of the'value' of the state. Chapter 2 introduces this model, Chapter 6 resumes the basic results.