This work demonstrates that research in the mainstream of knowledge acquisition leads to useful practical results. The contributors address knowledge modelling frameworks, the identification of generic components, methodology, architectures and applications.

CML: The commonKADS conceptual modelling language.- Evaluating a formal modelling language.- A comparison of two approaches to model-based knowledge acquisition.- Agent-based knowledge acquisition.- Beyond the knowledge level: Descriptions of rational behavior for sharing and reuse.- Local patching produces compact knowledge bases.- Components of problem solving and types of problems.- On a role of problem solving methods in knowledge acquisition.- Modeling plan recognition for decision support.- CUE: Ontology based knowledge acquisition.- KARO: An integrated environment for reusing ontologies.- From verification to modelling guidelines.- AFORIZM approach: Creating situations to facilitate expertise transfer.- How to combine data abstraction and model refinement: A methodological contribution in MACAO.- User centered knowledge-based system design: a formal modelling approach.- Validating at early stages with a causal simulation tool.- The SBF framework, 1989–1994: From applications to workplaces.- Applying the REKAP methodology to situation assessment.- Integration of learning into a knowledge modelling framework.- Knowledge level model of a configurable learning system.- Reflective, self-adaptive problem solvers.