Report 82-33 Welcome to the MRS TUTOR!!! This tutor is designed to introduce you to the syntax and basic database accessing functions of MRS. This document is a transcript of an interaction with the MRS tutor. Reprinted by permission of the author. Funding for this work was provided by ONR Contract N00014-81-K-0004. Representation languages provide a way to store and retrieve facts from a computer. Since English is a grammatically and textually ambiguous language, representation systems use a more formal language to describe the world. The way in which the words or symbols of a language are put together to form phrases and sentences is termed the "syntax" or "grammar" of the language.

I cis is the final report for Contract N-00014-79-C-03C2, covering the period of 15 March 1979 through 14 March 1982. The goal of the project was to develop methods for representing teaching and problem-solving knowledge in computer-based tutorial systems. One focus of the work was formulation of principles for managing a case method tutorial dialogue; the other major focus was investigation of the use of a production rule representation for the subject material of tutorial program. The main theme pursued by this research is that representing teaching and problemsolving knowledge separately and explicitly enhances the ability to build, modify and test complex tutorial programs. Two major corr Jter programs were constructed.

OMEN is an object-oriented programming system designed for use in a FRANI LISP or other similar programming environment. OMEN stands for OHiccr MANIPULATION ENVIRONNIFN r, and consists of a set of functions to be loaded on top of a!ASP system running MRS. The user can the use the functions provided by OMEN to create classes of objects, instances of those classes, and functions that operate on those objects, and to send messages to those objects. OMEN is similar in design and operation to the flavors system of Lisp Machine lisp and the LOOPS system for the Xerox Dolphin. OMEN was originally designed as a programming eny ironmcnt for an objectoriemed graphics system, but the system should be useful for many different applications. OMEN is not a programming language. It is a way of abstracting the data structures a program must use and the functions that operate on those data structures.

The Key idea is to represent explicitly and separately: a A. The limitations of MYCIN for application to teaching domain-independent diagnostic strategy in the form of meta-rules,

It is frequently observed that medicine.

Many RLL-1 units are directly used by one or more of the RLL-1 functions listed below. These special ones are enumerated below, following a depth first traversal of the RLL-1 Knowledge Base. Diagram #1 portrays a skeleton of this hierarchy, showing the subset relations joining these various classes.

The Most Important Gain: New Knowledge 18 10 Problems of Knowledge Engineering 19 10.1 The Lack of Adequate and Appropriate Hardware 19 10.2 Lack of Cumulation of Al Methods and Techniques 19 10.3 Shortage of Trained Knowledge Engineers 20 10.4 The Problem of Knowledge Acquisition 21 10.5 The Development Gap 21 11 Acknowledgments 22 1 1 Introduction: Symbolic Computation and Inference This paper will discuss the applied artificial intelligence work that is sometimes called "knowledge engineering". The work is based on computer programs that do symbolic manipulations and symbolic inference, not calculation. The programs I will discuss do essentially no numerical calculation. They discover qualitative lines-of-reasoning leading to solutions to problems stated symbolically.

This paper briefly outlines the difference between Branching on the bas of response was the first step coward traditional instructional programs and MAI.

It is noted that no one method is best with a view to the potential role of automated decision for all applications. However, emphasis is given to the limitations of early work that have made artificial intelligence techniques and knowledge aids in that domain 1611.

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.