Convergence in problem solving: a prelude to quantitative analysis

The paper describes a set of procedures that could be successfully used to restructure a mental model of diverse, connected constructs into a compact model suitable for quantitatively examining the key options available to the decision maker. These procedures can be applied in an interactive manner with a single decision maker or group of decision makers. The input to the convergence process is a connective map. A cognitive map is a signed, directed graph that links important concepts in the decision problem on the basis of probabilistic and informational dependence. It is assumed that the nodes in the graph have been labeled as decisions, uncertainties or values. The convergence procedures first structure the value and decision ends of the cognitive map so that each end properly reflects the value structure and a sample of varied and important options open to the decision maker. Sets of uncertain nodes are then identified, as good candidates for aggregation, or deletion. This identification is achieved by graph operations based upon specifically defined graphical structures and selected, qualitative reasoning techniques