Qualitative Bipolar Decision Frameworks Viewed as Pessimistic/Optimistic Utilities

A bipolar structure called BLF expresses knowledge about decisions in terms of decision principles that are ranked and polarized according to the utility of the consequences of these decisions. A BLF allows us to compare decisions under incomplete knowledge. For a given decision, the BLF returns a vector of utility/dis-utility in terms of achievement of positive/negative goals. Decisions are compared thanks to these vectors. In this paper we focus on the link between the uncertain knowledge aggregation made by the BLF and classical aggregation functions used in decision under uncertainty and multi-criteria approaches. The main benefit of a BLF is that thanks to the bipolar scale, positive and negative goals can be dealt with independently under their own point of view (each of them being either pessimistic or optimistic).

Automated summary

BLF, a bipolar structure, expresses knowledge about decisions through ranked decision principles based on utility of consequences, allowing comparison of decisions under incomplete knowledge. BLF returns a vector of utility/disutility for a decision in terms of achieving positive/negative goals, enabling comparison of decisions. The uncertain knowledge aggregation by BLF is linked to classical aggregation functions used in decision under uncertainty and multi-criteria approaches. The bipolar scale of BLF allows independent handling of positive and negative goals from both optimistic and pessimistic viewpoints.