Project Risk Management bya Probabilistic Expert System

Efficient applications of expert systems to project risk management problemsare seldom, if not unusual. In this paper we overcome this lack by using the probabilisticexpert system shell SPIRIT. The rule-based shell’s power in conditioning, inference andreasoning under incomplete information will work well on risk estimation and classification.A key characteristic of SPIRIT is the possibility to integrate project objectives into therisk management model. So known dependencies between risk variables can be modelledby the user if known beforehand, whereas hidden dependencies might be detected by theproper system. Because of the novelty of projects they suffer from incomplete informationand it is this incompleteness which SPIRIT handles at high information fidelity. Furthermoreundirected inference is possible, due to the undirected graphical structure in whichknowledge is acquired and processed...