Graph-Grammar Assistance for Automated Generation of Influence Diagrams

One of the most difficult aspects of modeling complex dilemmas in decision-analytic terms is composing a diagram of relevance relations from a set of domain concepts. Decision mod­ els in domains such as medicine, however, ex­ hibit certain prototypical patterns that can guide the modeling process. Medical con­ cepts can be classified according to semantic types that have characteristic positions and typical roles in an influence-diagram model. We have developed a graph-grammar produc­ tion system that uses such inherent interre­ lationships among medical terms to f9-cilitate the modeling of medical decisions.