Computational method for corrective mechanism of cognitive decision-making biases

When decisions are made by human beings these choices are often “predictably irrational”. A large number of different biases effect the human beings´ information processing systems. Because of the imperfect information processing system the decisions are imperfect as well, and very often some distortion appears in the solution. In our paper we propose a simple corrective mechanism for the loss aversion bias, presenting Kano´s quality model as a case study. An “interface” is placed between the input data and the optimizing algorithm and the input data are debiased instead of modifying the algorithm itself. The use of fuzzy numbers is adequate to model the loss aversion type bias and corrective tools. Computational results are presented as well to demonstrate the efficiency.