3. A method for automatically evaluating Bayesian network models for decision support as set forth in claim 2 , wherein the sampling is performed by a Monte Carlo algorithm.
3. A method for automatically evaluating Bayesian network models for decision support as set forth in claim 2 , wherein the sampling is performed by a Monte Carlo algorithm. 4. A method for automatically evaluating Bayesian network models for decision support, as set forth in claim 3 , wherein the outputted representation is a complete representation of probabilities of states for all conclusions given a particular set of combinations of conclusion states.