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PROGNOST: a customizable decision-support system

Most problems for which domain experts are hired depend on multiple information sources, which are often of a probabilistic nature. This certainly holds for the domain of selection and placement decisions. Decades of assessment research have shown that human experts are incapable of achieving high standards of accuracy in combining probabilistic information.

Over the last few years, a method of reasoning using probabilities, variously called belief networks, or Bayesian Networks (BN), has become the preferred Artificial Intelligence tool to build decision support systems. Bayesian probability theory is a branch of mathematical probability theory that allows one to model uncertainty about the world and outcomes of interest by combining theoretical knowledge, common-sense and observational evidence.

CogniMetrics, Inc. has developed a method to build and customize low-cost decision support systems for the domain of behavioral sciences using the Bayesian Network technology (see download in the middle column).

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