Hierarchical reasoning in QPNs based on network decomposition

Qualitative probabilistic networks(QPNs) have been designed for probabilistic reasoning in a qualitative way. As a consequence of their coarse level of representation detail, qualitative probabilistic networks do not provide for resolving trade-offs and typically yield ambiguous results upon inference, especially in large complicated networks, we propose an algorithm for computing more informative results for unresolved trade-offs. The algorithm derives significant efficiency building upon the idea of decomposing QPNs into subnetworks and reasoning hierarchically in virtue of enhanced representation.