The dynamics of probabilistic structural relevance

Probabilistic inference with a belief network in general is computationally expensive. Since the concept of structural relevance provides for identifying parts of a belief network that are irrelevant to a context of interest, it allows for alleviating to some extent the computational burden of inference: inference can be restricted to the network's relevant part. The structurally relevant part of a belief network, however, is not static. It may change dynamically as reasoning progresses. We address the dynamics of structural relevance and introduce the concept of an independence projection to capture these dynamics.