Expert Systems, Knowledge Based Engineering and Artificial Intelligence

1985 ◽  
pp. 125-127
Author(s):  
Vincent Walsh
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Knowledge Based ◽  
Knowledge Based Engineering

A survey of French developments in knowledge-based systems

1987 ◽  
Vol 2 (4) ◽  
pp. 287-295
Author(s):  
Jean-Claude Rault
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Computer Applications ◽  
Computer Architectures ◽  
Software Components ◽  
Industrialized Countries ◽  
Public Announcement ◽  
Knowledge Based ◽  
Fifth Generation ◽  
Industrial Communications

AbstractLike other industrialized countries, France is currently enjoying a vogue for artificial intelligence and, generally, for hardware and software components and structures which will be needed for the design and implementation of the computer applications of the 1990s.Since public announcement of MITI's Fifth Generation Project in October 1981, the French scientific and industrial communications have exhibited increasing enthusiasm for AI languages, expert systems, man-computer interaction, novel computer architectures, and knowledge-based computer systems as a whole. The choice of the Prolog language for the Japanese project has stimulated many French industrialists to be aware of the existence of a basic AI tool designed mainly in France.In spite of the present fashion, often maintained by the journalistic milieu, it would be inaccurate to say that the French fifth generation project goes back to the Japanese announcement. The MITI project has certainly been a catalyst of ministerial and industrial awareness, but the bulk of ongoing projects stem from earlier work most often funded by government agencies.In spite of the current thrust in AI and the centralizing habit in France, a “flagship” AI project cannot be identified. French Research and Development initiatives in artificial intelligence in general, and expert systems in particular, correspond more to a set of distinct projects. These frequently complement each other in technical scope and in their scientific and industrial objectives.

USING EXPERT SYSTEMS FOR IMAGE UNDERSTANDING

1987 ◽  
Vol 01 (02) ◽  
pp. 237-250 ◽  
Author(s):  
P. SUETENS ◽  
A. OOSTERLINCK
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Review Paper ◽  
Image Understanding ◽  
Interested Reader ◽  
Knowledge Based ◽  
Survey Papers ◽  
Application Fields

Expert systems and image understanding have traditionally been considered as two separate application fields of artificial intelligence (AI). In this paper it is shown, however, that the idea of building an expert system for image understanding may be fruitful. Although this paper may serve as a framework for situating existing works on knowledge-based vision, it is not a review paper. The interested reader will therefore be referred to some recommended survey papers in the literature.

Artificial Intelligence Systems in Aviation

2019 ◽  
pp. 1-26 ◽  
Author(s):  
Ramgopal Kashyap
Keyword(s):  
Artificial Intelligence ◽  
Traffic Management ◽  
Aircraft Engine ◽  
Air Traffic Management ◽  
Transit System ◽  
Agent Based ◽  
Knowledge Based ◽  
Control Framework ◽  
Knowledge Based Engineering ◽  
Artificial Intelligence Systems

The aim of this chapter is to research and fundamentally evaluate counterfeit shrewd frameworks to recognize for outperforming human insight in the flights and its conceivable ramifications. How artificial intelligence (AI) makes current airship framework incorporates an assortment of programmed control framework that guides the flight team in route, flight administration and enlarging the security qualities of the plane, and how building aircraft engine diagnostics ontology, air traffic management, and constraint programming (CP) is useful in ATM setting. How flight security can be enhanced through the advancement and usage of mining, utilizing its outcomes and knowledge-based engineering (KBE) approach in an all-encompassing methodology for use in airship reasonable outline, is discussed. The early recognizable proof and finding of mistakes, the study of huge information and its effect on the transportation business and enhanced transit system, the agent-based mobile airline search, and booking framework using AI are shown.

scholarly journals Expert Systems and Knowledge-Based Engineering (1984-1991): Implications for Instructional Systems Research

2014 ◽  
Vol 5 (2) ◽  
Author(s):  
Jo Ann Oravec
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Human Subjects ◽  
Instructional System ◽  
Good Deal ◽  
Essential Elements ◽  
Instructional Systems ◽  
Knowledge Based ◽  
Systems Research ◽  
Knowledge Based Engineering

Expert system technologies are varieties of artificial intelligence (AI) approaches in which decision-making knowledge is codified and modeled. This design case has the challenging task of characterizing this set of technologies during a particularly important period in its development (1984-1991), with an emphasis on a particular system that was used in food production environments by Campbell Soup. It analyzes the social and research impacts of early, pioneering information elicitation and processing strategies that focused on the distillation of the knowledge or know-how of individuals construed as experts in particular arenas, approaches broadly labeled as “knowledge-based engineering” (KBE). Widely-publicized notions of “thinking machines” and “canned experts” provided motivation for a good deal of early expert systems development (Feigenbaum & McCorduck, 1986), with accusations of “hype” often levied (Blair, 2002). This article historically situates these technological strategies in the period from 1984 though 1991, then links them with current instructional systems approaches that more fully involve collaborative elements as well as contextual perspectives. The motivation for this article is to explore how larger technological and social trends and assumptions can influence particular research efforts, especially in the richly interdisciplinary area of information systems. The article also explores the circumstances and consequences of “failures” of system development, with expert systems providing widely-discussed exemplars (Gill, 1995; Oravec & Plant, 1992). This article is rooted in the assumption that historically-informed perspectives can provide some underpinnings to the building of humane and sustainable research projects, particularly in areas that have human subjects and volatile contexts as essential elements. This article also addresses the continuing legacy of university curricula and business training initiatives that were shaped to accommodate expert system and KBE approaches in past decades. Discourse about human expertise generated by expert system efforts in 1984 through 1991 holds insights for current research and development, as well as signals potential sources of dysfunction of, and opposition to, future instructional system initiatives.

Psychological Issues in the Design of Expert Systems

1984 ◽  
Vol 28 (1) ◽  
pp. 73-77 ◽  
Author(s):  
Bruce W. Hamill
Keyword(s):  
Artificial Intelligence ◽  
Expert System ◽  
Expert Systems ◽  
Decision Aids ◽  
Non Profit ◽  
Psychological Issues ◽  
Knowledge Based ◽  
Artificial Intelligence Technology ◽  
Computer Based ◽  
Current Psychological

Recent advances in the artificial intelligence technology of knowledge-based expert systems have captivated the imaginations of designers, sponsors, and suppliers of computer-based systems in government and industry as well as researchers in university and non-profit laboratories where the technology originated. An expert system is essentially a way to capture the knowledge and expertise of a subject-matter expert and transfer it to a computer program in hopes of creating an “intelligent” computer system that will emulate the problem-solving and decision-making performance of the expert. Such systems are being built to serve as intelligent advisors and decision aids in a wide variety of application areas. We discuss conceptual issues underlying expert system design, with references to current psychological and artificial intelligence literature, and urge Consideration of these issues before undertaking development of expert systems.

A review of expert systems principles and their role in manufacturing systems

Robotica ◽  
1985 ◽  
Vol 3 (4) ◽  
pp. 279-287 ◽  
Author(s):  
P. T. Rayson
Keyword(s):  
Artificial Intelligence ◽  
Expert Systems ◽  
Manufacturing Systems ◽  
Knowledge Based Systems ◽  
Short Supply ◽  
Knowledge Based ◽  
Development Tools

SUMMARYThe objectives of this paper are twofold: The first is to briefly review for manufacturing engineers some of the early work undertaken by Artificial Intelligence researchers and the issues addressed which have culminated in today's “expert systems’ or ‘intelligent knowledge based systems’ (IKBS), as they are becoming known.The second is to indicate some early applications in manufacturing and to point out that any major success in this field requires long-term commitment, in depth familiarity with A.I. techniques and access to A.I. development tools, all of which are currently in short supply internationally.

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