This review examines two important works in decision analysis: Howard and Matheson's The Principles and Applications of Decision Analysis, and Winterfeldt and Edwards's "Decision Analysis and Behavioral Research.

The Computing Research Laboratory (CRL) at New Mexico State University is a center for research in artificial intelligence and cognitive science. Specific areas of research include the human-computer interface, natural language understanding, connectionism, knowledge representation and reasoning, computer vision, robotics, and graph theory. This article describes the ongoing projects at CRL.

Letters to the editor on the lack of a central index to the field's published works and the fact that many original works are not published in journals; praise for Letovsky article -- stimulating and amusing. felt subsequent letters to editors were full of bombastic indignation; criticism of Kasday letter about it and Bob Engelmore's weak support of the article; dualism in regards to Letovsky letter; and a reply to criticism by Letovsky, acknowledging diaristic form.

Johnson-Laird In a field choked with seemingly impenetrable jargon, Quick and thorough. Philip Johnson-Laird has done the impossible: written a By mixing forward and backward chaining, goal search book about how the mind works that requires no advance time can be shortenedramatically And, using GURU's knowledge of artificial intelligence, neurophysiology, or multiple rule firing capabilityou can refire rules psychology, providing the single best introduction to cognitive as values change GURU also comes equipped with science available. "Philip Johnson-Laird has that rare gift of being a cognitive seamlessly integrated 4th generation decision support scientist of the first order, yet he addresses himself to capabilitiesuch as data base, spreadsheet, and the deep classical issues in psychology, in the philosophy report generator

VT (vertical transportation) is an expert system for handling the design of elevator systems that is currently in use at Westinghouse Elevator Company. Although VT tries to postpone each decision in creating a design until all information that constrains the decision is known, for many decisions this postponement is not possible. In these cases, VT uses the strategy of constructing a plausible approximation and successively refining it. VT uses domain-specific knowledge to guide its backtracking search for successful refinements. The VT architecture provides the basis for a knowledge representation that is used by SALT, an automated knowledge-acquisition tool. SALT was used to build VT and provides an analysis of VT's knowledge base to assess its potential for convergence on a solution.

Real-time domains present a new and challenging environment for the application of knowledge-based problem-solving techniques. However, a substantial amount of research is still needed to solve many difficult problems before real-time expert systems can enhance current monitoring and control systems. In this article, we examine how the real-time problem domain is significantly different from those domains which have traditionally been solved by expert systems. We conduct a survey on the current state of the art in applying knowledge-based systems to real-time problems and describe the key issues that are pertinent in a real-time domain. The survey is divided into three areas: applications, tools, and theoretic issues. From the results of the survey, we identify a set of real-time research issues that have yet to be solved and point out limitations of current tools for real-time problems. Finally, we propose a set of requirements that a real-time knowledge-based system must satisfy.

This is Part 1 of a two-part article. Part 2 covers tort liability and computers as expert witnesses. It will appear in the Summer 1988 issue of AI Magazine. Technological developments that remove ever-increasing numbers of cognitive tasks from human control will alter the assumptions on which current legal rules are based. These rules will have a growing impact on AI researchers and entrepreneurs as their work reaches a growing audience of beneficiaries. In order to accommodate the needs of practitioners and their recipients, courts and lawmakers will be forced to reevaluate principles whose foundations were developed well before the implications of advanced technology could have been predicted. This article attempts to identify areas of law in which the need for accommodation will be greatest and provide some insight into the process and the direction of change.

This book is a collection of research papers covering a range of topics in expert systems and knowledge engineering.

We propose an approach for meeting real-time constraints in AI systems that views (1) time as a resource that should be considered when making control decisions, (2) plans as ways of expressing control decisions, and (3) approximate processing as a way of satisfying time constraints that cannot be achieved through normal processing. In this approach, a real-time problem solver estimates the time required to generate solutions and their quality. This estimate permits the system to anticipate whether the current objectives will be met in time. The system can then take corrective actions and form lower-quality solutions within the time constraints. These actions can involve modifying existing plans or forming radically different plans that utilize only rough data characteristics and approximate knowledge to achieve a desired speedup. A decision about how to change processing should be situation dependent, based on the current state of processing and the domain-dependent solution criteria. We present preliminary experiments that show how approximate processing helps a vehicle-monitoring problem solver meet deadlines and outline a framework for flexibly meeting real-time constraints.

Proceedings of the National Conference on Artificial Intelligence, 245-250