Problem-solving methods for knowledge-based systems establish the behavior of such systems by defining the roles in which domain knowledge is used and the ordering of inferences. Developers can compose problem-solving methods that accomplish complex application tasks from primitive, reusable methods. The key steps in this development approach are task analysis, method selection "from a library", and method configuration.

The IBROW³ project aims to support semi-automatic configuration of intelligent problem solvers out of reusable components. The project takes a holistic approach to reuse and is developing solutions for the various types of technologies required to make reuse both technically and economically feasible. These technologies include innovative software architectures, modelling languages, software libraries, brokering agents and methodologies. In this paper we focus on one particular aspect of the IBROW³ project: the specification of reusable library components. In particular, we illustrate a test case in which a pre-existing library of reusable components for parametric design is reformulated in terms of the framework and constructs provided by the IBROW³ modelling language. The exercise shows the advantages in terms of reusability and usability afforded by the IBROW³ approach. The proposed framework and language provide an effective organization for constructing ...

To make cost-effective use of a library of reusable problem-solving methods, developers must be able to quickly find and understand these methods, so that they can match their problem and knowledge base to a method in the reuse library. This match includes both finding the method and connecting to that executable software module via a set of mappings or mediators. To enable this match, builders of a reuse library must describe each method with a method-description language. We discuss a number of general desiderata for such a language. Our work focuses on one feature of the language: a precise specification of the input requirements of the method. This specification allows developers to correctly match their knowledge base to a pre-existing problem-solving method by formalizing the requirements of methods in the library. We propose an ontology for a method-description language, and present example specifications for two well-known problem-solving methods: propose-and-revise and cover-and-differentiate.

This document is composed of three parts. The first part describes WebOnto, a tool providing web-based visualisation, browsing and editing support for developing and maintaining ontologies and knowledge models specified in OCML. The description is user-oriented, in the sense that it is meant to provide guidance to a user, rather than to describe the tool from a scholarly perspective. The second part of the document describes OCML, an operational knowledge modelling language, which provides the underlying representation for the ontologies and knowledge bases which can be developed using WebOnto. This second part is a revised version of chapter 4 of (Motta, 1999). The third part (Appendix 1), gives more details about the interpreters and reasoning facilities provided by OCML

Much of the work on validation and verification of knowledge based systems (KBSs) has been done in terms of implementation languages (mostly rule-based languages). Recent papers have argued that it is advantageous to do validation and verification in terms of a more abstract and formal specification of the system. However, constructing such formal specifications is a difficult task. This paper proposes the use of formal specification languages for KBS-development that are closely based on the structure of informal knowledge-models. The use of such formal languages has as advantages that (i) we can give strong support for the construction of a formal specification, namely on the basis of the informal description of the system; and (ii) we can use the structural correspondence to verify that the formal specification does indeed capture the informally stated requirements. This paper has been submitted to the Journal of Human Computer Studies (formerly the Journal of Man Machine Studies)....

Abstract. This paper describes the design and implementation of a layered agent architecture for decision support applications in general and for distributed medical care in particular. Three important characteristics which shaped the agent design are identified: distribution of data and control, information uncertainty, and environment dynamism. To provide appropriate decision support in these circumstances the architecture combines a number of AI and agent techniques: a symbolic decision procedure for decision making with incomplete and contradictory information, a concept of accountability for task allocation, commitments and conventions for managing coherent cooperation, and a set of communication primitives for inter-agent interaction. 1.

This paper reports on the development of a realistic knowledge-based application using the MOBAL system. Some problems and requirements resulting from industrial-caliber tasks are formulated. A step-by-step account of the construction of a knowledge base for such a task demonstrates how the interleaved use of several learning algorithms in concert with an inference engine and a graphical interface can fulfill those requirements. Design, analysis, revision, refinement and extension of a working model are combined in one incremental process. This illustrates the balanced cooperative modeling approach. The case study is taken from the telecommunications domain and more precisely deals with security management in telecommunications networks. MOBAL would be used as part of a security management tool for acquiring, validating and refining a security policy. The modeling approach is compared with other approaches, such as KADS and stand-alone machine learning. What online ML can do for KA -...

The safety-critical nature of the application of knowledge-based systems to the field of medicine, demands the adoption of reliable engineering principles with a solid foundation for their construction. Logical languages with their inherent, precise notions of consistency, soundness and completeness offer such a foundation, thus promoting scrutinous engineering of medical knowledge. Moreover, logic techniques provide a powerful means for getting insight into the structure and meaning of medical knowledge used in medical problem solving. Unfortunately, logic is currently only used on a small scale for building practical medical knowledge-based systems. In this paper, the various approaches proposed in the literature are reviewed, and related to different types of knowledge and problem solving employed in the medical field. The appropriateness of logic for building medical knowledge-based expert systems is further motivated.

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The literature on validation and verification of knowledge-based systems contains a catalogue of anomalies for knowledge-based systems, such as redundant, contradictory or deficient knowledge. Detecting such anomalies is a method for verifying knowledge-based systems. Unfortunately, the traditional formulation of the anomalies in the literature is very specific to a rule-based knowledge representation, which greatly restricts their applicability. In this paper, we show how the traditional anomalies can be reinterpreted in terms of conceptual models (in particular KADS inference structures). For this purpose, we present a formalisation of KADS inference structures which enables us to apply the traditional rulebase anomalies to these inference structures. This greatly improves the usefulness of the anomalies, since they can now be applied to a much wider class of knowledge-based systems. Besides this reformulation and wider applicability of the traditional anomalies, further contribution...