Consequential reasoning in knowledge-based systems

Most knowledge-based systems rely on condition-action reasoning, traditionally represented in production rule format. For simple decision processes, this approach is adequate. However, good decision-making relies on the analysis of the consequences of the actions. None of the traditional knowledge representation formats provides a general framework for this type of analysis. In the work described here, a framework is outlined that incorporates knowledge structures and inference processes for dealing with consequential reasoning.