Knowledge Based Discrete Control Problems: A decision support approach

The aim of this paper is to applicate the theory and methods of Knowledge Based Systems (KBS) in combination with DSS concepts to develop more practical control models, to reach more efficient and user-friendly solution methods which determine closed optimal controls or control strategies, and to include learning and explanatory abilities into models and solutions procedures. The paper deals with the description of discrete control problems (DCP) in case of incomplete information (control under uncertainty). The well known models of DCP will be generalized by introducing a structured knowledge base. An architecture for a Knowledge Based Discrete Control Problem (KBDCP) will be proposed. It contains three interactive Expert Systems which are connected to each other.