Bounded rationality in decision making under uncertainty: Towards optimal granularity

Abstract

Starting from well-known studies by Kahmenan and Tversky, researchers have found many examples when our decision making seems to be irrational. We show that this seemingly irrational decision making can be explained if we take into account that human abilities to process information are limited. As a result, instead of the exact values of different quantities, we operate with granules that contain these values. On several examples, we show that optimization under such granularity restriction indeed leads to observed human decision making. Thus, granularity helps explain seemingly irrational human decision making.

Similar arguments can be used to explain the success of heuristic techniques in expert decision making. We use these explanations to predict the quality of the resulting decisions. Finally, we explain how we can improve on the existing heuristic techniques by formulating and solving the corresponding optimization problems.