Learning Meta-Rule Control of Production Systems from Execution Traces

In the last decade, work in Artificial Intelligence has stressed the importance of having both declarative and procedural forms of knowledge available. Recently, a number of workers have pointed out that procedural information can be regarded as control information which can be used to control the sequencing of application of the declarative components, and have remarked on the advantages of keeping these two types of information separate [see, for example, Sigart Newsletters #63, June 1977 and #70, Feb. 1980]. In the last few years we have been looking at the problem of automatically inferring this control component from the behaviour of the declarative component [7]. In this paper we describe briefly some experiments we have done, discuss some of the difficulties we have encountered, and show how they might be overcome

Psyxpert: An Expert system for aiding psychiatrists in the diagnosis of psychotic disorders

Psyxpert is an expert computer system designed to aid psychiatrists in the diagnosis of mental disorders when psychotic features are the prominent part of the presenting clinical picture. The knowledge base contains psychiatric knowledge in the form of production rules. The system uses a backward-chaining control strategy to guide the consultation. Psyxpert provides a menu-driven user interface and an explanation subsystem. The system uses certainty and importance measures to produce a diagnosis with an attached certainty factor and recommendations for further evaluation or therapy. Psyxpert is written in Virginia Tech HC Prolog and runs on Digital Equipment Corporation\u27s VAX 11/780 under the VMS operating system

Management. A continuing bibliography with indexes

This bibliography cites 604 reports, articles, and other documents introduced into the NASA scientific and technical information system in 1979 covering the management of research and development, contracts, production, logistics, personnel, safety, reliability and quality control. Program, project, and systems management; management policy, philosophy, tools, and techniques; decision making processes for managers; technology assessment; management of urban problems; and information for managers on Federal resources, expenditures, financing, and budgeting are also covered. Abstracts are provided as well as subject, personal author, and corporate source indexes

Artificial Intelligence and Human Error Prevention: A Computer Aided Decision Making Approach: Technical Report No. 4: Survey and Analysis of Research on Learning Systems from Artificial Intelligence

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryU.S. Department of Transportation / DOT FA79WA-4360 ABFederal Aviation Administratio