This paper gives an overview about the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling view and describe two approaches which considerably shaped research in Knowledge Engineering: Role-limiting Methods and Generic Tasks. To illustrate various concepts and methods which evolved in the last years we describe three modeling frameworks: CommonKADS, MIKE, and PROTG-II. This description is supplemented by discussing some important methodological developments in more detail: specification languages for knowledge-based systems, problem-solving methods, and ontologies. We conclude with outlining the relationship of Knowledge Engineering to Software Engineering, Information Integration and Knowledge Management.

Problem solving methods (PSMs) are domain-independent reasoning components, which specify patterns of behavior which can be reused across applications. While the availability of extensive PSM libraries and the emerging consensus on PSM specification languages indicate the maturity of the field, a number of important research issues are still open. In particular, very little progress has been achieved on foundational and methodological issues. Existing libraries of PSMs lack a clear theoretical basis and only provide weak support for the method development process, usually in the form of informal guidelines. In this paper we will address these issues by illustrating a framework which characterizes PSMs in terms of problem commitments, problem-solving paradigms and domain assumptions. This framework provides i) a theoretical foundation for situating PSM research and individual PSMs, as well as ii) an organization which allows us to characterize method development and selection as a process of navigating through a three-dimensional space (defined by the three components of our framework). Individual moves through this space are specified by means of adapters. In the paper we will illustrate these ideas in detail, with examples taken from parametric design problem solving. 1.

. Much of the work on ontologies in AI has focused on describing some aspect of reality: objects, relations, states of affairs, events, and processes in the world. A goal is to make knowledge sharable, by encoding domain knowledge using a standard vocabulary based on the ontology. A parallel attempt at identifying the ontology of problem-solving knowledge has a goal of sharable problem-solving methods. For example, when one is dealing with abductive inference problems, the following are some of the terms that occur in the representation of problem-solving methods: hypotheses, explanatory coverage, evidence, likelihood, plausibility, composite hypothesis, etc. Method ontology is, in good part, goal- and method-specific. Generic Tasks," Heuristic Classification," Task-specific Architectures," Task-method Structures," Inference Structures" and Task Structures" are representative bodies of work in the knowledge-systems area that have focused on domainindependent problem-solving methods. Ho...

Assumptions of problem-solving methods refer to necessary applicability conditions of problem-solving methods, indicating that a problem-solving method is only applicable to realize a task, if the assumptions are met. In principle, such assumptions may refer to any kind of condition involved in a problem-solving method's applicability, including its required domain knowledge. In this paper, we propose a conceptual organization for assumptions of problem-solving methods and suggest a formal language to describe them. For illustration we take examples from the Propose & Revise problem-solving method and from diagnosis.

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 ...

Mostly, papers on problem-solving methods focus on the description of reasoning strategies and discuss their underlying assumptions as a side aspect. We take a complementary point of view and focus on these underlying assumptions as they play three important roles: first, assumptions are necessary to characterise the precise competence of a problem-solving method in terms of the tasks that can be solved by it, and in terms of the domain knowledge that is required by it. Second, assumptions are necessary to enable tractable problem solving for complex problems. Third, assumptions are necessary for appropriate interaction of the problem solver with its environment. Their introduction and refinement can be used to develop new problem-solving methods, or to adapt existing ones according to task and domain-specific circumstances of a given application. For this purpose, one requires a framework for dealing with these assumptions. This paper makes a step in this direction by sum...

. In this document we present a library of generic, reusable components whose purpose is to support the specification and operationalization of classification problem solvers. In addition, it is envisaged that this library will provide a test case for future version of the IBROW component brokering and configuration system. The library has been specified in the OCML modelling language, according to the IBROW framework for reuse. It comprises ontologies, task specifications and problem solving methods. In the document we discuss our approach to modelling classification problem solving, we describe the various parts of the library, we illustrate its application to a pre-existing domain model and we discuss related work and open issues. Contact Information Email: {e.motta, w.lu}@open.ac.uk 1. INTRODUCTION Research on problem solving methods (Benjamins and Fensel, 1998) and ontologies (Gruber, 1995) aims (among other things) to identify and formalise classes of generic compone...

Automated handling of tutoring and training functions in educational systems requires the availability of articulate domain models. In this article we further develop the application of qualitative models for this purpose. A framework is presented that defines a key role for qualitative models as interactive simulations of the subject matter. Within this framework our research focuses on automating the diagnosis of learner behaviour. We show how a qualitative simulation model of the subject matter can be reformulated to fit the requirements of general diagnostic engines such as GDE. It turns out that, due to the specific characteristics of such models, additional structuring is required to produce useful diagnostic results. A set of procedures is presented that automatically maps detailed simulation models into a hierarchy of aggregated models by hiding non-essential details and chunking chains of causal dependencies. The result is a highly structured subject matter model that enables the diagnosis of learner behaviour by means of an adapted version of the GDE algorithm. An experiment has been conducted that shows the viability of the approach taken, i.e., given the output of a qualitative simulator the procedures we have developed automatically generate a structured subject matter model and subsequently use this model to successfully diagnoses learner behaviour. 2000 Elsevier Science B.V. All rights reserved.

Ontologies and problem-solving methods are promising candidates for reuse in Knowledge Engineering. Ontologies define domain knowledge at a generic level, while problem-solving methods specify generic reasoning knowledge. Both type of components can be viewed as complementary entities that can be used to configure new knowledge systems from existing, reusable components. In this paper, we give an overview of approaches for ontologies and problem-solving methods. 1 Introduction In 1991, the ARPA Knowledge Sharing Effort [NFF 91] envisioned a new way in which intelligent systems could be built. They proposed the following: "Building knowledgebased systems today usually entails constructing new knowledge bases from scratch. It could be done by assembling reusable components. Systems developers would then only need to worry about creating the specialized knowledge and reasoners new to the specific task of their system. This new system would interoperate with existing systems, us...

. The paper introduces a formal approach for the specification and verification of knowledge-based systems. We identify different elements of such a specification: a task definition, a problem-solving method, a domain model, an adapter, and assumptions that relate these elements. We present abstract data types and a variant of dynamic logic as formal means to specify these different elements. Based on our framework we can distinguish several verification tasks. In the paper, we discuss the application of the Karlsruhe Interactive Verifier (KIV) for this purpose. KIV was originally developed for the verification of procedural programs but it fits well for our approach. We illustrate the verification process with KIV and show how KIV can be used as an exploration tool that helps to detect assumptions necessary to close the gap between the task definition and the competence of a problemsolving method. 1 Introduction During the last years, several conceptual and formal specification tech...