Bayesian advocates of expected utility maximization use sets of probability distributions to represent very different ideas. Strict Bayesians insist that probability judgment is n...
For cancers with more than one risk factor, the sum of probabilistic estimates of the number of cancers attributable to each individual factor may exceed the total number of cases...
Minh Ha-Duong, Elizabeth Casman, M. Granger Morgan
For many problems there is only suf£cient prior information for a Bayesian decision maker to identify a class of possible prior distributions. In such cases it is of interest to ...
The paper deals with basic issues regarding the measurement of relevant types of uncertainty and uncertainty-based information in theories that represent imprecise probabilities o...
When modeling real-world decision-theoretic planning problems in the Markov decision process (MDP) framework, it is often impossible to obtain a completely accurate estimate of tr...
Karina Valdivia Delgado, Scott Sanner, Leliane Nun...