This paper proposes a new method for solving Bayesian decision problems. The method con-sists of representing a Bayesian decision problem as a valuation-based system and applying a fu-sion algorithm for solving it. The fusion algo-rithm is a hybrid of local computational methods for computation of marginals of joint probability distributions and the local computational meth-ods for discrete optimization problems.
Decision support systems have emerged over five decades ago to serve decision makers in uncertain co...
A significant class of decision making problems consists of choosing actions, to be carried out simu...
Abstract: The paper describes the extensive educational system for the field of Bayesian decision-ma...
This paper proposes a new method for representing and solving Bayesian decision problems. The repres...
AbstractWe propose a method for computing the range of the optimal decisions when the utility functi...
Focussed Bayesian fusion is a local Bayesian fusion technique by that high costs caused by Bayesian ...
A new algorithm for development of quasi-optimal decision trees, based on the Bayes theorem, has bee...
We investigate algorithms for different steps in the decision making process, focusing on systems wh...
This book is an introduction to the mathematical analysis of Bayesian decision-making when the state...
We present a unifying framework for the global optimization of functions which are expensive to eval...
We present a unifying framework for the global optimization of functions which are expensive to eval...
A Bayesian decision theoretic approach to directional multiple hypotheses problem
Solving symmetric Bayesian decision problems is a computationally intensive task to perform regardle...
The last five years have seen a surge in interest in the use of techniques from Bayesian decision th...
In this paper an algorithm based on the concepts of genetic algorithms that uses an estimation of a...
Decision support systems have emerged over five decades ago to serve decision makers in uncertain co...
A significant class of decision making problems consists of choosing actions, to be carried out simu...
Abstract: The paper describes the extensive educational system for the field of Bayesian decision-ma...
This paper proposes a new method for representing and solving Bayesian decision problems. The repres...
AbstractWe propose a method for computing the range of the optimal decisions when the utility functi...
Focussed Bayesian fusion is a local Bayesian fusion technique by that high costs caused by Bayesian ...
A new algorithm for development of quasi-optimal decision trees, based on the Bayes theorem, has bee...
We investigate algorithms for different steps in the decision making process, focusing on systems wh...
This book is an introduction to the mathematical analysis of Bayesian decision-making when the state...
We present a unifying framework for the global optimization of functions which are expensive to eval...
We present a unifying framework for the global optimization of functions which are expensive to eval...
A Bayesian decision theoretic approach to directional multiple hypotheses problem
Solving symmetric Bayesian decision problems is a computationally intensive task to perform regardle...
The last five years have seen a surge in interest in the use of techniques from Bayesian decision th...
In this paper an algorithm based on the concepts of genetic algorithms that uses an estimation of a...
Decision support systems have emerged over five decades ago to serve decision makers in uncertain co...
A significant class of decision making problems consists of choosing actions, to be carried out simu...
Abstract: The paper describes the extensive educational system for the field of Bayesian decision-ma...