Causal knowledge elicitation based on elicitation failures

The paper presents an approach to causal knowledge elicitation supported by a tool directly used by the domain expert. This knowledge elicitation approach is characterized by trying to guess an interpretation of the knowledge entered by the expert. The tool (initially general), as it is used, self customizes its guessing capability, remembers failures in guessing (in order to avoid similar failures in the future) and when they occur elicits their explanations. Even in this case, elicitation is supported by guessing on the basis of previous similar failures. The resulting overall effect is that the tool digs up tenaciously causal knowledge from the expert´s mind, playing in this way a cooperative role for model building