Second-Order Risk Constraints

This paper discusses how numerically imprecise information can be modelled and how a risk evaluation process can be elaborated by integrating procedures for numerically imprecise probabilities and utilities. More recently, representations and methods for stating and analysing probabilities and values (utilities) with belief distributions over them (second order representations) have been suggested. In this paper, we are discussing some shortcomings in the use of the principle of maximising the expected utility and of utility theory

• Type: Conference
• Year: 2008
• Where: FLAIRS
• Authors: Love Ekenberg, Aron Larsson, Mats Danielson
• Keywords: Artificial Intelligence, FLAIRS 2008, Imprecise Probabilities, Risk Evaluation Process, Second Order Representations