Using information theory in risk analysis

Two basic concepts of information theory: entropy and conditional entropy are applied in the framework of stochastic lienar programming problems. These applications illustrate some of the powerful implications of information theory in modelling various forms of adaptive and risk-averse behaviour. A class of robust decisions which are less sensitive to worst case scenarios is also developed to show the usefulness of information theory as a nonparametric approach.