Multiresolutional hierarchical decision support systems

Abstract

Decision support systems gain better performance and higher accuracy by the virtue of building multiresolutional (multigranular, multiscale) representation, and employing multiscale behavior generation subsystem (planning and control). The latter are equipped by devices for unsupervised learning that adjust their functioning to the results of self-identification. We demonstrate that planning and learning are joint processes. The author's intention is to emphasize that the concepts of multiresolutional representation (MR) and multiresolutional decision support (MR-DSS) probably have in common a general significance that crosses the boundaries of particular domains of applications and disciplines. The paper explores this phenomenon. The ubiquity of a principle that somehow persistently delivers benefits to many areas of knowledge and technology seems to be more important than a habit to follow the pigeonhole principle of paper presentation.