MEBRS: A Multiagent Architecture for an Experience Based Reasoning System

Dutch research on knowledge-based instructional systems: Introduction to the special issue

This paper presents a low cost knowledge based system (KBS) framework for design of bending die. Considerations for development of KBS are discussed at some length. The proposed framework divides the task of development of expert system into different modules for major activities of bending die design. The procedure of development of KBS modules is also described at length. Production rules for each module are recommended to be coded in the AutoLISP language and designed to be loaded into the prompt area of AutoCAD or through user interface created using Visual Basic. Each module of the proposed framework is user interactive. Development of one module of the proposed framework is also described at length. This module is capable to assess manufacturability of bending sheet metal parts. An illustrative example is also included to demonstrate the usefulness of this module. The proposed system framework is flexible enough to accommodate new acquired knowledge. As the proposed system is implementable on a PC having AutoCAD software, therefore its low cost of implementation makes it affordable even by small scale sheet metal industries.

Financial industry is a core industry in Hong Kong. The business systems in financial institutes are widely applied throughout their front, mid, and back office. The system specialist who supports these systems must have finance and information-systems knowledge. This multi-disciplinary requirement leads to difficulties in finding capable candidates. It is reasonably assumed that a knowledge-based system (KBS) with the intelligence of a system specialist can assist a helpdesk to support the business systems. However, KBS development involves many known issues. In particular, the uncertainties of collected knowledge should be discussed and remodelled iteratively until the final knowledge set is close to the actual knowledge. Although the literature states that it is theoretically feasible to use Unified Modelling Language (UML) on knowledge acquisition, case studies on this area to date have been insufficient, hence this research experiment UML on developing a KBS for supporting business systems in a financial institute. The method of using UML diagrams is documented throughout the study. The results show that the UML was useful in different stages of KBS development. The case study articulates how the KBS helps to solve business system problems in the company. In summary, this paper can shed light on future research in using UML for KBS development.

Since the architecture of a software system constrains the quality attributes, the decisions taken during architectural design have a large impact on the resulting system. An architectural design method is presented that employs iterative evaluation and transformation of the software architecture in order to satisfy the quality requirements. Architecture evaluation is performed by using scenarios, simulation, mathematical modelling and experience-based reasoning. The architecture can be transformed by imposing an architectural style, imposing an architectural pattern, using a design pattern, converting a quality requirement to functionality and by distributing quality requirements. The method has evolved through its application in several industrial projects.

This paper presents a framework called logical knowledge object (LKO), which is taken as a basis of the dependable development of knowledge based systems(KBSs). LKO combines logic programming and object-oriented programming paradigms, where objects are viewed as abstractions with states, constraints, behaviors and inheritance. The operational semantics defined in the style of natural semantics is simple and clear. A hybrid knowledge representation amalgamating rule, frame, semantic network and blackboard is available for both most structured and flat knowledge. The management of knowledge bases has been formally specified. Accordingly, LKO is well suited for the formal representation of knowledge and requirements of KBSs. Based on the framework, verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs. In addition, LKO provides a methodology for the development of KBSs, applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements, and to provide multiple abstract models of the domain, where formal methods might be used at each abstract level.

Research in verification and validation (V&V) of knowledge based systems (KBS) has emerged as a distinct field in the last decade and is intended to address issues associated with KBS quality aspects and to credit such applications to the same degree as conventional applications. Part of the knowledge and techniques developed are now ready to be transferred to industry for the implementation of software certification. Certification is probably the most advanced use of the V&V methods, techniques and knowledge that have been developed so far. The paper approaches the challenging issues of certifying the knowledge base (KB) component of a KBS. KB certification uses a number of different certification methods such as static analysis, testing, inspection, and modeling to assess the quality of the KB component. Although these methods are currently used in KBS development, it is not yet clear how they would be applied by an independent certification organization to arrive at a pass/fail decision. The article discusses the components of KB certification and identifies application areas directly connected with industrial needs.

Knowledge Based System (KBS) is a problem solving approach that makes use of human knowledge in decision strategies. Modeling and representing imperfect human knowledge associated with uncertainty is an important task in KBS development. There are various types of uncertainty, and randomness and fuzziness are among the most important. Handling hybrid uncertainty in one KBS is critical to support real world applications. Knowware System (KWS) is an intelligent tool designed to support application developers in constructing customized hybrid KBS without requiring developers being familiar with relevant intelligent techniques. It is essential for KWS to construct corresponding inference structure in resulting KBS and process the inference with hybrid uncertainty. To fulfill this requirement the extended Truth Value Flow Inference (TVFI) and Interval-Valued Confidence (IVC) have been defined and developed as ambedded mechanisms of KWS, and the hybrid logic has been adopted for the framework of handling hybrid uncertainty.This chapter discusses the IVC for the inference in hybrid KBS constructed by KWS with hierarchical knowledge representation. The knowledge content (precise or imprecise) represented in multiple units of knowledge hierarchy and the confidence obtained during inference process are treated as at two levels separately but simultaneously based on the extended TVFI. With the basic form of IVC, a fuzzy truth value is represented as a fuzzy number defined as a three-parametric triangular type-1 fuzzy set on the unit interval [0, 1]. The inference with both fuzzy truth and probability results an Extended Interval-Valued Confidence (EIVC) which is an interval type-2 fuzzy set on [0, 1] having the probability as an uncertainty measure on the fuzzy truth. The main focus of discussion will be put on interval-valued confidence. To provide the background of discussion, the KWS scheme, the extended TVFI and the concepts of hybrid logic will be briefly introduced.KeywordsUncertaintyRandomnessFuzzinessKnowwareSystemHybridLogicInterval-Valued Confidence

Knowledge-based safety training system (KBSTS)— A prototype implementation

The Log Quality Monitoring System (LQMS) is a medium-sized knowledge-based system that was developed to address the problem of providing real-time assistance to the wireline field engineer. The authors discuss the motivation for the project, review the major decisions that were made, detail how they affected the direction of the project, and identify the basic lessons that were learned. The research version of LQMS was developed at Schlumberger-Doll Research over a period of about three and a half years. The project successfully dealt with several thorny issues in the development of knowledge-based systems: multiple domain experts, real time constraints, embedded environment, coordination and communication of multiple knowledge sources, and technology transfer. The project evolved from an exploratory, rapid prototyping style of development to a more traditional specify/design/implement/test methodology. Much of this evolution was driven by the field testing and technology transfer requirements of the later stages of the project. >

This article alms to provide biology educators with some simple Ideas of how techniques used In the development of Knowledge-Based Systems (KBS) can assist in the analysis of classification problems in school biology. The major focus of this paper is not to review KBS technology, but to show how some of the tools of thought which can be used to design and develop these systems can help biology teachers. In so doing, some valuable didactic ideas that may be transferred are described. The paper looks at rule-based systems and applies ideas to some examples of biological classification namely, classifying vertebrates and bird wings. Following on from this, some more general Issues are discussed about concepts and classification

An integrated methodology for knowledge-based system development

The development, validation and implementation of knowledge-based systems

The development of an online knowledge-based expert system for machinability data selection

It is pointed out that matching potentially strong developers with appropriate knowledge-based system (KBS) development projects can optimize an organization's allocation of scarce human and financial resources. In a broader sense, it can contribute to supporting an organization's effort to develop the creative computer systems necessary for competitive positioning. To test this hypothesis, the authors report the results of a study of 91 developers new to KBS technology. This group served as a test bed to explore an answer to the question 'can we learn what kind of developer creates a successful (i.e., innovative and useful) knowledge-based system?' In other words, it there a 'successful KBS developer' profile? The results provide tentative answers that need to be reconsidered with more rigorous further study. >

The ability of Patient Dependency Systems to provide information for staffing decisions and budgetary development has been demonstrated. In addition, they have become powerful tools in modern hospital management. This growing interest in Patient Dependency Systems has renewed calls for their automation. As advances in Information Technology and in particular Knowledge-Based Engineering reach new heights, hospitals can no longer afford to ignore the potential benefits obtainable from developing and implementing Patient Dependency Knowledge-Based Systems. Experience has shown that the vast majority of decisions and rules used in the Patient Dependency method are too complex to capture in the form of a traditional programming language. Furthermore, the conventional Patient Dependency Information System automates the simple and rigid bookkeeping functions. On the other hand Knowledge-Based Systems automate complex decision making and judgmental processes and therefore are the appropriate technology for automating the Patient Dependency method. In this paper a new technique to automate Patient Dependency Systems using knowledge processing is presented. In this approach all Patient Dependency factors have been translated into a set of Decision Rules suitable for use in a Knowledge-Based System. The system is capable of providing the decision-maker with a number of scenarios and their possible outcomes. This paper also presents the development of Patient Dependency Knowledge-Based Systems, which can be used in allocating and evaluating resources and nursing staff in hospitals on the basis of patients' needs.