Cognitive map composition, derivation, and focus generation for distributed group decision support

The author first introduces a partial taxonomy for cognitive maps and the concepts of NPN logic and NPN relations which serve as the theoretical basis for this work. Then, C-type neural networks are proposed as a dynamic model for cognitive maps. Based on these models, a distributed system, D-POOL, for cognitive map composition, derivation, and focus generation is presented; its application to distributed group decision support is illustrated. D-POOL first pools distributed cognitive maps into an NPN relation which retains both negative and positive assertions from multiple decision makers or groups in a unified representation to gain high cognitive transparency and integrity. Then, an NPN relation is encoded into a C-type neural model from which new cognitive maps can be generated as decision supports from a nebulous environment. The potential utility of the system is demonstrated by two application examples