Theorem Proving Vision Robotics Information Processing Psychology Learning and Inductive Inference Planning and Related Problem-solving Techniques A. Natural Language Processing Ovnrview The most common way that human beings communicate Is by speaking or writing In one of the "natural" languages, like English, French, or Chinese. Computer programming languages, on the other hand, seem awkward to humans. These "artificial" languages are designed to have a rigid format, or syntax, so that a computer program reading and compiling code written In an artificial language can understand what the programmer means. In addition to being structurally simpler than natural languages, the artificial languages can express easily only those concepts that are important In programming: "Do this then do that," "See it such and such Is true," etc. The things that can be expressed In a language are referred to as the semantics of the language. The research on understanding natural language described in this section of the Handbook is concerned with programs that deal with the full range of meaning of languages like English.

Those of us involved In the creation of the Handbook of Artificial Intelligence, both writers and editors, have attempted to make the concepts, methods, tools, and main results of artificial Intelligence research accessible to a broad scientific and engineering audience. Currently, Al work Is familiar mainly to its practicing specialists and other interested computer scientists. Yet the field Is of growing interdisciplinary interest and practical Importance. With this book we are trying to build bridges that are easily crossed by engineers, scientists in other fields, and our own computer science colleagues. In the Handbook we Intend to cover the breadth and depth of Al, presenting general overviews of the scientific issues, as well as detailed discussions of particular to -hniques and Important Al systems.

Currently Al work is familiar mainly to Its practicing specialists and other interested computer scientists. Yet tho field is of growing interdisciplinary Interest and practical importance. With this book we are trying to build bridges that are easily crossed by engineers, scientists in other fields, ond our own computer science colleagues. In the Handbook we intend to cover the breadth and depth of Al, presenting general overviews of the scientific issues, as well as detailed discussions of particular techniques and important Al systems. Throughout we have tried to keep In mind the reader who is not a specialist In Al.

A clinical investigator graphical capabilities which can plot specific parameters for a keeping the records of his study patients on such a system can patient over time 1126]. However, it is in the analysis of stored use the program's statistical capabilities for data analysis.

This paper is a "final report" on the first version of the CRYSALIS project. As such, we will summarize the current state of the system and show where we plan to go with it. We have found that a design (in the software eng ineer ing sense) is a valuable tool for the evaluation and augmentation of a program, even when the design is done ex post facto. Using such a design, we discuss the major flaws of the existing system and how to correct them. Finally, we show how the architecture of this system could be useful for certain other task domains.

In the early days of computing, these goals were central to the new discipline called cybernetics [126], [2]. Over the past two decades, progress toward these goals has come from a variety of fields - notably computer science, psychology, adaptive control theory, pattern recognition, and philosophy. Substantial progress has been made in developing techniques for machine learning in highly restricted environments.

Because of the recent - echnological advances in computer networks and communications, and because of the cost reduction of computer hardware, there has been a great interest in distributed data bases including some attempts at actual implementations. In this paper, we will first define what we mean by a distributed data base. Then we will give some of the reasons why people are so interested in this new field. After classifying the different types of distributed data bases, we will describe the current areas of research. Finally, we will give an annotated bibliography that lists the most important papers in thi:3 area.

He also taught the biochemistry course that I finally took, two years after finishing my Ph.D. David J. States deserves much of the credit as well. In the three years we have been working together, he greatly extended my understanding of not only what biologists know, but how they think. He has read several drafts of this chapter and made helpful suggestions. David Landsman, Mark Boguski, Kalí Tal and Jill Shirmer have also read the chapter and made suggestions. Angel Lee graciously supplied the gel used in Figure 4. Of course, all remaining mistakes are my responsibility.

We have divided this area into categories and cross-indexed the references accordingly.

The editors have provided him with special introductory sections as a ing guide to a thorough understand of the reports.