Validating the Knowledge Base of a Therapy Planning System

1989 ◽  
Vol 28 (01) ◽  
pp. 36-50 ◽  
Author(s):  
M. A. Shwe ◽  
S. W. Tu ◽  
L. M. Fagan
Keyword(s):  
Expert System ◽  
Cancer Therapy ◽  
Expert Systems ◽  
Knowledge Base ◽  
Knowledge Bases ◽  
Planning System ◽  
Test Cases ◽  
Parallel Model ◽  
Therapy Planning ◽  
System Knowledge

Abstract:Validation of expert system knowledge bases has proved to be difficult. This paper presents a description of a system called ScriptGen that generates test data for validating the knowledge base of the ONCOCIN cancer therapy planning system. Because of the size and complexity of the ONCOCIN knowledge base, we require tools for automated validation. ScriptGen, which applies techniques developed in testing both traditional software and expert systems, uses a parallel model of the ONCOCIN knowledge base and its own inference engine to generate test cases. We derived the limits of the system from a study that seeded errors into an existing knowledge base.

scholarly journals Method for Attack Tree Data Transformation and Import Into IT Risk Analysis Expert Systems

2020 ◽  
Vol 10 (23) ◽  
pp. 8423
Author(s):  
Donatas Vitkus ◽  
Jonathan Salter ◽  
Nikolaj Goranin ◽  
Dainius Čeponis
Keyword(s):  
Expert System ◽  
Risk Analysis ◽  
Expert Systems ◽  
Knowledge Base ◽  
Automated Analysis ◽  
Knowledge Bases ◽  
It Security ◽  
Security Risk ◽  
Attack Tree ◽  
Attack Trees

Information technology (IT) security risk analysis preventatively helps organizations in identifying their vulnerable systems or internal controls. Some researchers propose expert systems (ES) as the solution for risk analysis automation since risk analysis by human experts is expensive and timely. By design, ES need a knowledge base, which must be up to date and of high quality. Manual creation of databases is also expensive and cannot ensure stable information renewal. These facts make the knowledge base automation process very important. This paper proposes a novel method of converting attack trees to a format usable by expert systems for utilizing the existing attack tree repositories in facilitating information and IT security risk analysis. The method performs attack tree translation into the Java Expert System Shell (JESS) format, by consistently applying ATTop, a software bridging tool that enables automated analysis of attack trees using a model-driven engineering approach, translating attack trees into the eXtensible Markup Language (XML) format, and using the newly developed ATES (attack trees to expert system) program, performing further XML conversion into JESS compatible format. The detailed method description, along with samples of attack tree conversion and results of conversion experiments on a significant number of attack trees, are presented and discussed. The results demonstrate the high method reliability rate and viability of attack trees as a source for the knowledge bases of expert systems used in the IT security risk analysis process.

Principles and practice in verifying rule-based systems

1992 ◽  
Vol 7 (2) ◽  
pp. 115-141 ◽  
Author(s):  
Alun D. Preece ◽  
Rajjan Shinghal ◽  
Aïda Batarekh
Keyword(s):  
Expert System ◽  
Knowledge Base ◽  
State Of The Art ◽  
Knowledge Bases ◽  
Order Logic ◽  
First Order Logic ◽  
Rule Based ◽  
First Order ◽  
Rule Bases ◽  
System Knowledge

AbstractThis paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The first part describes four types of anomaly: redundancy, ambivalence, circularity, and deficiency. We consider rule bases which are based on first-order logic, and explain the anomalies in terms of the syntax and semantics of logic. The second part presents a review of five programs which have been built to detect various subsets of the anomalies. The four anomalies provide a framework for comparing the capabilities of the five tools, and we highlight the strengths and weaknesses of each approach. This paper therefore provides not only a set of underlying principles for performing knowledge base verification through anomaly detection, but also a survey of the state-of-the-art in building practical tools for carrying out such verification. The reader of this paper is expected to be familiar with first-order logic.

scholarly journals IMPLEMENTASI SISTEM PAKAR DIAGNOSA KERUSAKAN PADA CANON NP6650XX MENGGUNAKAN METODA DEMPSTER SHAFER

2016 ◽  
Vol 1 (2) ◽  
Author(s):  
Khaerul Manaf
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
System Development ◽  
Computer Software ◽  
Software Tool ◽  
Theory Of Knowledge ◽  
Monitor Screen ◽  
System Knowledge

An expert system is a computer software that has a knowledge base. Where knowledge is taken from several experts with experience working for years on a particular field of expertise. Expert systems easier to develop and specifications are not too difficult, so it can be used by computers that exist todayThe purpose of this study to design a software tool in diagnosing damage to the machine canon NP 6650XX which creates the appearance of an error code on the monitor screen machine using Dempster Shafer Method. To achieve this, research is conducted by collecting the theories associated with this machine, based on the theory of knowledge, undertake steps that expert system development, identification, conceptualization, formalization, implementation and testingThe result is a software that can provide information about damage to the machine canon NP 6650XX which such damage can lead to the appearance of an error code on the monitor screen machine.  Keywords: Expert System, Knowledge, Canon Machinery, Error, Dempster Shafer.

Development of rules in expert systems for the analysis and evaluation of telecommunications

2017 ◽  
Vol 12 (2) ◽  
pp. 47-63 ◽  
Author(s):  
T. S. Abbasova
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
Noise Immunity ◽  
Knowledge Bases ◽  
Analysis And Evaluation ◽  
Telecommunications Infrastructure ◽  
Telecommunication Systems ◽  
Characteristic Features ◽  
Developing Knowledge

Typical malfunctions that may occur in telecommunication systems due to the failure to meet the noise immunity requirements, as well as the characteristic features that can identify these problems, are analyzed. In the process of developing the knowledge base for the expert system for assessing the telecommunications infrastructure, the existing tools for developing knowledge bases have been improved.

Diabetes Mellitus - Evaluating the Diagnostic Probabilities

2011 ◽  
pp. 169-177
Author(s):  
Adi Armoni
Keyword(s):  
Diabetes Mellitus ◽  
Decision Making ◽  
Expert System ◽  
Expert Systems ◽  
Knowledge Base ◽  
Decision Maker ◽  
Knowledge Bases ◽  
Bayesian Theory ◽  
Logical Conclusion ◽  
Human Decision

The article examines the behavior of the human decision-maker. It surveys research in which about 90 physicians specializing in various fields and with different degrees of seniority participated. It tackles the question of whether it is possible to found the majority of the knowledge bases of the expert systems on the Bayesian theory. We will discuss the way of decision making conforming to the probabilities evaluated according to the Bayesian theory. The logical conclusion, therefore, is that the development of a knowledge base for an expert system founded on probabilities calculated in accordance with the Bayesian theory must be carried out in a controlled manner and depend on the parameters mentioned above.

Fundamentals of creating MIVAR expert systems

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Intelligent Systems ◽  
Autonomous Robots ◽  
Support Systems ◽  
Knowledge Bases ◽  
Computer Engineering

Methodological and applied issues of the basics of creating knowledge bases and expert systems of logical artificial intelligence are considered. The software package "MIV Expert Systems Designer" (KESMI) Wi!Mi RAZUMATOR" (version 2.1), which is a convenient tool for the development of intelligent information systems. Examples of creating mivar expert systems and several laboratory works are given. The reader, having studied this tutorial, will be able to independently create expert systems based on KESMI. The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Mivar databases and rules

2021 ◽  
Author(s):  
Oleg Varlamov
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Expert System ◽  
Expert Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Knowledge Bases ◽  
Data Models ◽  
Active Network ◽  
New Model

The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

Knowledge-acquisition tools with explicit problem-solving models

1993 ◽  
Vol 8 (1) ◽  
pp. 5-25 ◽  
Author(s):  
William Birmingham ◽  
Georg Klinker
Keyword(s):  
Expert System ◽  
Problem Solving ◽  
Expert Systems ◽  
Knowledge Acquisition ◽  
Knowledge Base ◽  
Code Generation ◽  
System Development ◽  
Generalization Error ◽  
Domain Experts ◽  
The Past

AbstractIn the past decade, expert systems have been applied to a wide variety of application tasks. A central problem of expert system development and maintenance is the demand placed on knowledge engineers and domain experts. A commonly proposed solution is knowledge-acquisition tools. This paper reviews a class of knowledge-acquisition tools that presuppose the problem-solving method, as well as the structure of the knowledge base. These explicit problem-solving models are exploited by the tools during knowledge-acquisition, knowledge generalization, error checking and code generation.

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