This paper reports on an investigation into a formal language for specifying kads models of expertise. After arguing the need for and the use of such formal representations, we discuss each of the layers of a kads model of expertise in the subsequent sections, and define the formal constructions that we use to represent the kads entities at every layer: order-sorted logic at the domain layer, meta-logic at the inference layer, and dynamic-logic at the task layer. All these constructions together make up (ml) 2 , the language that we use to represent models of expertise. We illustrate the use of (ml) 2 in a small example model. We conclude by describing our experience to date with constructing such formal models in (ml) 2 , and by discussing some open problems that remain for future work. 1 Introduction One of the central concerns of "knowledge engineering" is the construction of a model of some problem solving behaviour. This model should eventually lead to the construction of a...

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)....

This paper outlines the result of the discussions that took place at the Ninth Knowledge Acquisition Workshop in Banff, Canada, in February 1995 (KAW'95). The authors attempt to summarise the current efforts in using the Conceptual Graphs (CGs) for knowledge acquisition and modelling expertise. The work on CGKAT, [KADS]->(ON)->[CG], CG-DESIRE, and MODEL-ECS are briefly outlined. In addition to this, a list of limitations as seen by the Knowledge Acquisition Community is outlined, together with a list of requirements that is specifically solicited by the KA-Community to enable them to actively utilise CG as a modelling and representation formalism for building knowledge-based systems. We further outlined how and where CG could make effective contributions in the areas of knowledge acquisition. Finally, we present the areas of research that is severely lacking and the future work to be carried out, in particular, work on evaluation of the methodologies, systems, and tools using CG for kn...