Explaining Qualitative Decision under Uncertainty by Argumentation

Proceedings of the AAAI Conference on Artificial Intelligence, 21

Volume

Technical Papers

Knowledge Representation and Logic

Decision making under uncertainty is usually based on the comparative evaluation of different alternatives by means of a decision criterion. In a qualitative setting, pessimistic and optimistic criteria have been proposed. In that setting, the whole decision process is compacted into a criterion formula on the basis of which alternatives are compared. It is thus impossible for an end user to understand why an alternative is good, or better than another. Besides, argumentation is a powerful tool for explaining inferences, decisions, etc. This paper articulates optimistic and pessimistic decision criteria in terms of an argumentation process that consists of constructing arguments in favor/against decisions, evaluating the strengths of those arguments, and comparing pairs of alternatives on the basis of their supporting/attacking arguments.