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.

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.

ICOT: An Integrated C-Object Tool for Knowledge-Based Programming

1998 ◽  
Vol 06 (03) ◽  
pp. 273-293 ◽  
Author(s):  
Hyung Jeong Yang ◽  
Jae Dong Yang ◽  
Yeongho Kim
Keyword(s):  
Expert System ◽  
Object Oriented ◽  
Fuzzy Information ◽  
Major Drawback ◽  
Rule Based ◽  
Knowledge Based ◽  
Complex Engineering ◽  
Knowledge Based Engineering ◽  
Current Rule ◽  
New Framework

In this paper, an Integrated C-Object Tool, namely ICOT, is proposed for knowledge-based programming. A major drawback of current rule-based expert system languages is that they have difficulty in handling composite objects as a unit of inference. An object-oriented model is a powerful alternative to complement the drawback. Each of these alone cannot capture all the semantics of knowledge, particularly in complex engineering domains. For a knowledge-based approach to be effective, both the object-oriented paradigm and the rule-based mechanism may need to be integrated into one framework. The framework may also need to support manipulation of fuzzy knowledge to model the real world as close as possible. Three types of fuzzy information are identified, and a proper way of representing and inferencing them is developed. ICOT provides a new framework into which rule-based deduction, object-oriented modeling, and fuzzy inferencing are combined altogether. This can become especially useful for developing knowledge-based engineering applications.

COOP: A SELF-ASSESSMENT BASED APPROACH TO COOPERATING EXPERT SYSTEMS

1992 ◽  
Vol 01 (02) ◽  
pp. 175-204 ◽  
Author(s):  
SHASHI SHEKHAR ◽  
C. V. RAMAMOORTHY
Keyword(s):  
Expert System ◽  
Problem Solving ◽  
Expert Systems ◽  
Computational Method ◽  
Global Knowledge ◽  
Self Assessment ◽  
Knowledge Based ◽  
Contract Net ◽  
Distributed Problem Solving ◽  
Geographically Distributed

Conventional Expert System Shells do not help in developing AI programs for large applications like automated factories, which require multi-disciplinary knowledge and which are geographically distributed. To support these applications, a shell must provide tools for a knowledge-based system to (i) reason about the need for cooperation, (ii) understand global knowledge to locate relevant expert systems and (iii) select appropriate cooperation plans. Contemporary approaches like Blackboard [1], Contract-net [2] and Distributed problem solving [3] help in exploring alternative cooperation plans without any reasoning about the need for cooperation and understanding of global knowledge. Coop [4] support cooperation models to characterize three essential decisions in the cooperation process. It provides a computational method to decide if an expert system needs to consult with other expert systems. We provide techniques select appropriate cooperation plans.

Knowledge-based advisory system for flexible pavement routine maintenance

1993 ◽  
Vol 20 (1) ◽  
pp. 154-163 ◽  
Author(s):  
Paulette B. Hanna ◽  
Awad S. Hanna ◽  
Thomas A. Papagiannakis
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Practical Experience ◽  
Asphalt Pavements ◽  
Pavement Maintenance ◽  
Advisory System ◽  
Knowledge Based ◽  
Other Information ◽  
Maintenance Decisions ◽  
Asphalt Concrete Pavement

One of the most pressing problems facing Canada is the condition of roadway infrastructure. Making good maintenance decisions requires years of practical experience and judgement. Expert systems have great potential for solving pavement maintenance problems that usually require significant human expertise for solution. Expert systems, also known as knowledge-based systems, have been used as a means for conveying pavement maintenance knowledge gained through research and field experience to individuals responsible for maintaining asphalt pavements. An expert system is defined as an interactive computer program which documents judgement, experience, intuition, and other information in order to provide knowledgeable advice.This paper describes the development of PMAS, a pavement maintenance advisory system, which can assist highway engineers in planning effective flexible or asphalt concrete pavement maintenance strategies. The system uses two alternative commercial expert system shells. The system questions the user in a multiple-choice format in everyday English and (or) by using pictures. The user responds by selecting one or more of the choices provided by the system. At the end of the consultation session, the system displays the most appropriate maintenance strategy along with its life expectancy. PMAS facilitates the decision-making process and could serve as a consultant for field engineers. Key words: expert system, knowledge-based system, pavement maintenance.

scholarly journals Rule Based and Supervisory Training Approach To Develop Expert System Tool For Detecting Lung Cancer Disease

2010 ◽  
Vol 9 (1) ◽  
pp. 1-11
Author(s):  
K. Balachandran ◽  
R. Anitha
Keyword(s):  
Lung Cancer ◽  
Expert System ◽  
Expert Systems ◽  
Medical Attention ◽  
Cancer Disease ◽  
Rule Based ◽  
Knowledge Based ◽  
Training Approach ◽  
Dreaded Disease ◽  
Rule Based Approach

Knowledge-based expert systems, or expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Lung cancer is one of the dreaded disease in the modern era. It is responsible for the most cancer deaths in both men and women throughout the world. Early diagnosis and timely treatment are imperative for the cure. Longevity and cure depends on early detection. This paper gives on insight to identify the forget group of people who are suffering or susceptible to suffer lung cancer disease. Seeking proper medical attention con be initiated based on the findings. Expert system tool developed, to find this target group based on the non-clinical parameters. Symptoms and risk factors associated with Lung cancer ore token as the basis of this study. This expert system basically works on the rule based approach to collect the data. Then Supervisory learning approach is used to infer the basic data. Once sufficient knowledge base is generated the system can be made to adopt in unsupervised learning mode.

Design of an Android-Based Tropical Disease Diagnosis Expert System Design Using a Combined Method of Forward Chanining and Backward Chaining

2015 ◽  
Vol 1 (1) ◽  
pp. 43-50
Author(s):  
Muhammad Fahmi Hidayah
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Disease Diagnosis ◽  
Reference Book ◽  
Combined Method ◽  
Specific Domain ◽  
Backward Chaining ◽  
Forward Chaining ◽  
Knowledge Based ◽  
Specific Symptoms

A doctor or medical scholar needs a reference book to learn how to diagnose tropical diseases. This reference book is sometimes a hassle if you have to carry it everywhere. This reference book is also impractical if you have to search it first to find the symptoms and diseases you want to study. So that we need a system to make it easier for doctors and medical scholars to study the science of diagnosis and look for symptoms and diseases. Expert systems are knowledge-based programs that provide expert quality solutions to problems in a specific domain. This expert system is used in the fields of medicine, agriculture, business, and others. Expert systems in the field of medicine make it easy to identify diseases suffered by patients through the symptoms present in the patient. This expert system helps doctors make diagnoses to convince doctors about the results of the diagnosis. The expert system in this study uses a combined method. The combined method is forward chaining and backward chaining. The forward chaining method is used to determine specific symptoms that appear, while the backward chaining method is used to trace general symptoms that arise from specific symptoms that have been previously selected. The result of combining these methods provides a diagnostic percentage of 100%. Meanwhile, the user's assessment of the system gives a good response.

Development of an Expert Engineering Module for Determination of Ultrasonic Probe Position on the Weld Joint of Plate

2009 ◽  
Vol 83-86 ◽  
pp. 1306-1314 ◽  
Author(s):  
D. Shahriari ◽  
J Jodaki ◽  
V. Jandaghi Shahi ◽  
J Darban Falak
Keyword(s):  
Expert System ◽  
Critical Assessment ◽  
Probe Position ◽  
Ultrasonic Probe ◽  
Knowledge Based ◽  
Three Samples ◽  
Probe Location ◽  
Knowledge Based Engineering ◽  
Inspection Techniques

Ultrasound based inspection techniques are used extensively throughout industry for detection of flaws in engineering materials. The range and variety of imperfections encountered is large and critical assessment of location, size, orientation and type is often difficult. The research presented in this paper has resulted in a knowledge-based engineering module, which was developed software for determining ultrasonic probe location precisely and detecting of the welded sections completely. The criteria for diagnosing these positions, which have been classified into different groups, included in type of material, thickness, geometry of welded section, couplant material, angle probes and etc. The expert system can display the limits that probe must be moved which caused an inspection welded section thoroughly. This study was conducted using three samples including different materials with V groove welded sections for verifying this expert system. Finally this module is very suitable in Q.C. labs and different industries for detection of flaws.

Applications of expert system building tools in structural design

1991 ◽  
Vol 18 (3) ◽  
pp. 493-503
Author(s):  
K. M. Sakr ◽  
M. U. Hosain
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
Structural Design ◽  
Simple Design ◽  
Inference Mechanism ◽  
System Building ◽  
Knowledge Based ◽  
Real World Applications ◽  
Basic Concepts

This paper summarizes the basic concepts of expert systems and describes some of the applications of three commercially available expert system tools. The function of the various components of the tools is explained using simple design examples. It is concluded that a tool can be employed to develop useful expert systems for real-world applications, provided factual and heuristic material is available for creating a knowledge base. Key words: artificial intelligence, knowledge-based expert systems, knowledge base, inference mechanism, expert system building tools, structural design, applications of expert system building tools.

Sign in / Sign up

Export Citation Format

Share Document