Causal model-based knowledge acquisition tools: discussion of experiments

Abstract The aim of this paper is to study causal knowledge and demonstrate how it can be used to support the knowledge acquisition process. The discussion is based on three experiments we have been involved in. First, we identify two classes of Causal Model-Based Knowledge Acquisition Tools (CMBKATs): bottom-up designed causal models and top-down designed causal models. We then go on to discuss the properties of each type of tool and how they contribute to the whole knowledge acquisition process.