Add to ORKGA supra-Bayesian (SB) wants to combine the information from a group of k experts to produce her distribution of a probability theta. Each expert gives his counts of what he thinks are the numbers of successes and failures in a sequence of independent trials, each with probability a of success. These counts, used as a surrogate for each expert's own individual probability assessment (together with his associated level of confidence in his estimate), allow the SE to build various plausible conjugate models. Such models reflect her beliefs about the reliability of different experts and take account of different possible patterns of overlap of information between them. Corresponding combination rules are then obtained and compared with other mo...
A number of models have been recently proposed in the Bayesian non-parametric literature for dealing...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Where a decision-maker has to rely on expert opinions a need for a normative model to combine these ...
A supra-Bayesian (SB) wants to combine the information from a group of k experts to produce her dist...
We review recent developments in applying Bayesian probabilistic and statistical ideas to expert sys...
We develop a new outlook on the use of experts’ probabilities for inference, distinguishing the info...
Abstract: Efficient multiple-participant decision making [1] relies on a cooperation of partici-pant...
Information that is elicited from experts can be treated as `data', so can be analysed using a Bayes...
AbstractWe address the problem of information fusion in uncertain environments. Imagine there are mu...
The problem of combining information related to I binomial experiments, each having a distinct proba...
We resolve a useful formulation of the question how a statistician can coherently incorporate the in...
SIGLEAvailable from British Library Document Supply Centre-DSC:DXN011313 / BLDSC - British Library D...
We consider the problem of combining opinions from different experts in an explicitly model-based wa...
none3noIn every real-world domain where reasoning under uncertainty is required, combining informati...
Expert systems often employ a weight on rules to capture conditional probabilities. For example, in ...
A number of models have been recently proposed in the Bayesian non-parametric literature for dealing...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Where a decision-maker has to rely on expert opinions a need for a normative model to combine these ...
A supra-Bayesian (SB) wants to combine the information from a group of k experts to produce her dist...
We review recent developments in applying Bayesian probabilistic and statistical ideas to expert sys...
We develop a new outlook on the use of experts’ probabilities for inference, distinguishing the info...
Abstract: Efficient multiple-participant decision making [1] relies on a cooperation of partici-pant...
Information that is elicited from experts can be treated as `data', so can be analysed using a Bayes...
AbstractWe address the problem of information fusion in uncertain environments. Imagine there are mu...
The problem of combining information related to I binomial experiments, each having a distinct proba...
We resolve a useful formulation of the question how a statistician can coherently incorporate the in...
SIGLEAvailable from British Library Document Supply Centre-DSC:DXN011313 / BLDSC - British Library D...
We consider the problem of combining opinions from different experts in an explicitly model-based wa...
none3noIn every real-world domain where reasoning under uncertainty is required, combining informati...
Expert systems often employ a weight on rules to capture conditional probabilities. For example, in ...
A number of models have been recently proposed in the Bayesian non-parametric literature for dealing...
Bayesian Belief Networks are a powerful tool for combining different knowledge sources with various ...
Where a decision-maker has to rely on expert opinions a need for a normative model to combine these ...