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.

We describe the ingredients of an intelligent agent (a broker) for configuration and execution of knowledge systems for customer requests. The knowledge systems are configured from reusable problemsolving methods that reside in digital libraries on the Internet. The approach followed amounts to solving two subproblems: (i) the configuration problem which implies that we have to reason about problem-solving components, and (ii) execution of heterogeneous components. We use CORBA as the communication infrastructure.

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 World-Wide Web is changing the nature of software development to a distributive plug & play process. This requires a new way of managing software by so-called intelligent software brokers. The aim of the European IBROW3 project is to develop an intelligent brokering service that enables third party knowledge-component reuse through the World-Wide Web. Suppliers provide libraries of knowledge components adhering to some standard, and customers can consult these libraries -- through intelligent brokers -- to configure a knowledge system suited to their needs by selection and adaptation. IBROW3 integrates research on heterogeneous databases, interoperability and web technology with knowledge-system technology and ontologies. The aim is to develop a broker that can handle web requests for classes of knowledge system (e.g. diagnostic systems) by accessing libraries of reusable problem-solving methods on the Web, and selecting, adapting and configuring these methods in accor...

. Problem-solving methods are means to describe the inference process of knowledge-based systems. During the last years, a number of these problemsolving methods have been identified that can be reused for building new systems. However, problem-solving methods require specific types of domain knowledge and introduce specific restrictions on the tasks that can be solved by them. These requirements and restrictions are assumptions that play a key role in reusing problem-solving methods, in acquiring domain knowledge, and in defining the problem that can be tackled by the knowledge-based systems. In the paper, we discuss the different roles, assumptions play in the development process of knowledge-based systems and provide a survey of assumptions used by diagnostic problem solving. We show how such assumptions introduce target and bias for goal-driven machine learning and knowledge discovery techniques. 1 INTRODUCTION During the last years, Problem-solving methods (PSMs) have become quit...

In this paper, we present a case study of KBS engines built thanks to our knowledge-based system (KBS) development platform Lama. The Lama platform enables the software-level composition of KBS engines (hence PSMs) for a given task from reusable reasoning blocks. This paper emphasizes engine design activity and shows how our platform helps easily create new engines or modify existing ones. Indeed, designers need help to build the problem-solving method (PSM) of an engine, appropriately for an application domain. The current available tools neither integrate designers' knowledge at the right level, nor ooeer development, integration and testing facilities to implement KBS engines. Our experience tackles problems such as PSM and ontology design and (partial) reuse. This involves aspects such as the choice of an appropriate set of reasoning blocks to cover the needs of a problem-solving task, with the right level of granularity. As a first experimental field, we focus on program supervision...