Decision-making oriented aggregation of nodes in influence diagrams

The high-level decision-making is time-consuming in a large, complex circumstance. The decision-maker needs to consider many factors whatever they are in same domain or not. Influence diagram (ID) is an effective tool to help people make a strategic decision. In a large influence diagram, the high-level decision-maker doesn't need to know the details, and he only needs to know the overall effects of the decisions made in each domain. Starting from this real application, it is necessary to aggregate the nodes in a domain into one block in an influence diagram. In this paper, we are to discuss the aggregation of nodes in influence diagrams. In order to aggregate nodes, we have to partition the influence diagram into blocks first. Each block is composed of nodes which contact each other strongly and contact other nodes loosely. Since the influence diagram has different types of nodes, we have to partition these types of nodes respectively. Based on the relationships among nodes, we aggregate each block into a new node. Further, we combine the blocks with different types of nodes and get a new influence diagram. Preliminary experiments show the feasibility of our proposed methods.