Developing an expert system to assist in control system design

This paper addresses the problem of how to develop an expert system that is able to design or to assist in the design of a control system. The discussion includes how to structure the expert system, how to choose the relationship between the symbolic and numerical processor and how to divide the work among the expert system, the computer aided control systems analysis package and the design engineer. A prototype intelligent design associated is presented and an example of a compensator design is given.     

Developing an expert system for predicting alluvial channel geometry using ANN

Cross section geometry of stable alluvial channels usually is estimated by simple inaccurate empirical equations, because of the complexity of the phenomena and unknown physical processes of regime channels. So, the main purpose of this study is to evaluate the potential of simulating regime channel treatments using artificial neural networks (ANNs). The process of training and testing of this new model is done using a set of available published filed data (371 data numbers). Several statistical and graphical criterions are used to check the accuracy of the model in comparison with previous empirical equations. The multilayer perceptron (MLP) artificial neural network was used to construct the simulation model based on the training data using back-propagation algorithm. The results show a considerably better performance of the ANN model over the available empirical or rational equations. The constructed ANN models can almost perfectly simulate the width, depth and slope of alluvial regime channels, which clearly describes the dominant geometrical parameters of alluvial rivers. The results demonstrate that the ANN can precisely simulate the regime channel geometry, while the empirical, regression or rational equations can’t do this. The presented methodology in this paper is a new approach in establishing alluvial regime channel relations and predicting cross section geometry of alluvial rivers also it can be used to design stable irrigation and water conveyance channels.     

Knowledge sources for an intelligent algebra tutor

The focus of this paper is on the underlying knowledge base for an intelligent tutorial system for high-school algebra problems. We present a model of problem solving flexible enough to account for a variety of problem-solving behaviors and general enough to allow new problem domains to be defined easily. The model is based upon the analysis of protocols between students and expert tutors. We show how student errors can be monitored and remediated using the model, and we provide an approach to understanding problem difficulty that can be used to generate challenging problems and also provides a mechanism for planning their solution.     

Developing maintainable expert systems using case-based reasoning

Abstract: Maintainability problems associated with traditional software systems are exacerbated in rule-based systems. The very nature of that approach — separation of control knowledge and data-driven execution — hampers maintenance. While there are widely accepted techniques for maintaining conventional software, the same is not true for rule-based systems. In most situations, both a knowledge engineer and a domain expert are necessary to update the rules of a rule-based system. This paper presents, first, an overview of the software engineering techniques and object-oriented methods used in maintaining rule-based systems. It then discusses alternate paradigms for expert system development. The benefits of using case-based reasoning (from the maintenance point of view) are illustrated through the implementation of a case-based scheduler. The main value of the scheduler is that its knowledge base can be modified by the expert without the assistance of a knowledge engineer. Since changes in application requirements can be given directly to the system by the expert, the effort of maintaining the knowledge base is greatly reduced.     

Developing expert systems builders in logic programming

We intend to develop a set of kits to build Expert Systems using Prolog. Two principal modules, a Knowledge Base acquisition and consultation subsystems are now presented. Several knowledge representation structures and mixed inference mechanisms are proposed for the sake of system efficiency. Finally some explanation capabilities derived accordingly with used inference methods are also implemented and presented.     

Representing complex knowledge in an intelligent machine tutor

Knowledge representation remains a serious issue for researchers of intelligent tutoring systems. Two areas of knowledge representation that are particularly difficult are domain and teaching knowledge. This article discusses and gives example solutions to these knowledge engineering issues and also addresses issues that relate to up-scaling existing intelligent tutoring technology to practical levels so that tutoring systems can be brought into the real world.     

Developing sound tutor training for online writing centers: creating productive peer reviewers

It is our experience that tutors trained for face-to-face writing centers are not adequately prepared for the challenges they encounter working with online writing centers. The purpose of our article is to provide an overview—especially for administrators, developers, and tutors new to electronic tutoring environments—of the issues and considerations unique to online tutoring that training programs need to address. In our discussion, we hope to engender enthusiasm for online tutoring by discussing three aspects of online tutoring: appreciating text-only environments, developing procedures for responding online, and creating appropriate roles for online tutors. We offer suggestions about how to address these three aspects in online tutor training, and we suggest that addressing these issues leads to an understanding of the online tutor as a productive peer reviewer.     

Towards an intelligent tutor for a complex mathematical domain

Abstract: The domain of mathematics has played a special part in the evolution of Intelligent Tutoring Systems (ITSs), beginning as far back as the 1950s when conventional Computer Assisted Instruction (CAI) came into being. A brief historical review of this evolutionary process is presented, followed by a selective survey of some of the intelligent tutoring systems in the mathematics domain as well as some of their shortcomings and the criticisms levelled against them. The work achieved so far towards the realisation of an intelligent tutoring system for a complex mathematical domain is presented. A major conclusion is that the 'mal-rule' methodology for developing tutoring systems may lend itself to simple 'primitive' domains, but its credibility is seriously questioned when it is applied to more 'complex' domains. An alternative methodology is proposed to solve this problem, together with an illustration.     

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Specifying an expert system

The success of numerous expert systems in practical applications warrants a more formal approach to their development and evaluation. Reliability assurance of expert systems requires a methodology for the specification and evaluation of these systems. Expert systems are a new class of software system, but some traditional techniques of software development may be adapted to their construction. However, the specification of an expert system differs from that of a more traditional software program in that parts of the specification are permitted to be only partially described when development starts.

Specifications have two important purposes: as contracts between suppliers and clients, and as blueprints for implementation. A specification consists of a problem specification and a solution specification. The problem specification plays the role of contract and states explicitly what the problem to be solved is, and the constraints that the final product must satisfy. The solution specification plays the role of blueprint and has two major aspects: analyzing how a human expert solves the problem, and proposing an equivalent automated solution. We propose an approach to the specification of expert systems that is flexible, yet rigorous enough to cover the important features of a wide range of potential expert system applications. We describe fully each of the components of an expert system specification and we relate specification to the issues of evaluation and maintenance of expert systems.     

The STAR system: an interactive pronunciation tutor for young children

Between 1990 and 1998, the Speech Research Unit at the Defence Evaluation and Research Agency (DERA), and Hereford and Worcester County Council Education Department, a U.K. local education authority, conducted research into the use of speech recognition technology in an interactive computer-based pronunciation tutor for 5–7 year-old primary school children. The goal of the project was to develop a robust, autonomous system that would enable a child to practice the pronunciation of a given set of words by speaking them to a computer, which provided immediate feedback on whether the pronunciation was acceptable. This paper describes the development of the underlying speech recognition technology, the prototype real-time system which was developed, and the results of pilot trials of the system in a U.K. primary school.     

Implementing a CMC tutor group for an existing distance education course

Abstract ‘Artificial Intelligence for Technology’ (T396) is a distance learning course provided by the Open University of the UK using face‐to‐face tutorials. In 1997 a pilot study was undertaken of a computer‐mediated communication (CMC) tutor group which consisted of volunteers from around the UK. The student feedback raised a number of issues including: the need for a distinct function for the tutor group conference, the role of and demands on the tutor, and the benefits perceived by students. It is suggested that some issues arise from a conflict of cultures each with their own implicit assumptions. The traditional face‐to‐face tutorial model is sometimes at variance with the demands of the new CMC based tuition.     

Firewalls: an expert roundtable

The Internet's increasing popularity has brought with it a downside: more severe security risks. With initial funding from the US government, the computer security community has developed products called firewalls that help protect users' systems from harm when they connect to the Internet and other networks beyond their control. Dozens of commercial firewall products on the market worldwide are enjoying healthy sales. The authors examine the effectiveness of firewalls and suggest improvements and alternatives that can make your system safer     

Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2Math

In order for an Intelligent Tutoring System (ITS) to correct students’ exercises, it must know how to solve the same type of problems that students do and the related knowledge components. It can, thereby, compare the desirable solution with the student’s answer. This task can be accomplished by an expert system. However, it has some drawbacks, such as an exponential complexity time, which impairs the desirable real-time response. In this paper we describe the expert system (ES) module of an Algebra ITS, called PAT2Math. The ES is responsible for correcting student steps and modeling student knowledge components during equations problem solving. Another important function of this module is to demonstrate to students how to solve a problem. In this paper, we focus mainly on the implementation of this module as a rule-based expert system. We also describe how we reduced the complexity of this module from O(n^d) to O(d), where n is the number of rules in the knowledge base, by implementing some meta-rules that aim at inferring the operations students applied in order to produce a step. We evaluated our approach through a user study with forty-three seventh grade students. The students who interacted with our tool showed statistically higher scores on equation solving tests, after solving algebra exercises with PAT2Math during an approximately two-hour session, than students who solved the same exercises using only paper and pencil.     

ANEMIA: an expert consultation system

Anemia is a knowledge-based consultation program for anemic states. It has been built using an artificial intelligence programming scheme, called EXPERT, which was developed at Rutgers University. At present, ANEMIA is able to provide assistance in the diagnosis and management of 64 disease entities. They include iron deficiency anemias, anemias due to chronic disorders, thalassemias, hemolytic anemias, arigenerative anemias, and a few other miscellaneous conditions. ANEMIA was tested against a data base of 220 retrospective and 100 new cases and the overall accuracy in the diagnostic performance was pretty good. Our intent is that ANEMIA ultimately will be able to serve as surrogate for the hematologist with the nonhematologist physician-user.