抄録
A knowledge-based decision support system (DSS) is presented, which aids a decisionmaker in the face of complex societal problems in formulating alternatives and evaluating them based on a problem-oriented knowledge represented as cognitive maps, i.e., networks of causal relations in its knowledge base. The knowledge concerning such problems is so enormous and complicated that each alternative cannot have unique consequence, that is, it affects the goals to be attained both in promoting (positive) and suppressing (negative) ways through causal relations. In this paper, a method to separately quantify those dual effects is developed taking account that the effect is weakened in propagating through sequential intermediate causal relations and is strengthened in integrating a numbler of sequential effects existing in parallel. Then, from those quantities two attributes are derived concerning intensity of total effects and predominance of both effects, and the preference characteristic over those attributes is discussed. Using those ideas, a knowlede-based DSS is constructed, which can rank sets of alternatives according to their contribution to the decisionmaker's own utility by extracting his own personal attitude for his problem through interactive conversations.
