Representing and eliciting knowledge about uncertain evidence and its implications

A reasoning system and associated assessment methodology built on a natural schema for an evidential argument are discussed. This argument schema is based on the underlying causal chains linking conclusions and evidence. The framework couples a probabilistic calculus with qualitative approaches to evidential reasoning. The resulting knowledge structure leads to a natural assessment methodology in which the expert first specifies a qualitative argument from evidence to conclusion. Next the expert specifies a series of premises on which the argument is based. Invalidating any of these premises would disrupt the causal link between evidence and conclusion. The final step is the assessment of the strength of the argument, in the form of degrees of belief for the premises underlying the argument. The expert may also explicitly adopt assumptions affecting the strength of evidential arguments. A higher-level `metareasoning´ process is described, in which assumptions underlying the strength and direction of evidential arguments may be revised in response to conflict