Knowledge Sharing and Negotiation Support in Multiperson Decision Support Systems

A number of DSS for supporting decisions by more than one person have beenproposed. These can be categorized by spatial distance (local vs. remote),temporal distance (meeting vs. mailing), commonality of goals (cooperationvs. bargaining), and control (democratic vs. hierarchical). Existingframeworks for model management in single-user DSS seem insufficient forsuch systems.This paper views multiperson DSS as a loosely coupled system of model anddata bases which may be human (the DSS builders and users) or computerized.The systems components have different knowledge bases and may havedifferent interests. Their interaction is characterized by knowledgesharing for uncertainty reduction and cooperative problem-solving, andnegotiation for view integration, consensus-seeking, and compromise.Requirements for the different types of multiperson DSS can be formalizedas application-level communications protocols. Based on a literaturereview and recent experience with a number of multiperson DSS prototypes,artificial intelligence-based message-passing protocols are compared withdatabase-centered approaches and model-based techniques, such asmulticriteria decision making