Incremental Compilation of Bayesian networks
  Most methods of exact probability propagation in Bayesian networks do not
carry out the inference directly over the network, but over a secondary
structure known as a junction tree or a join tree (JT). The process of
obtaining a JT is usually termed {sl compilation}. As compilation is usually
viewed as a whole process; each time the network is modified, a new compilation
process has to be carried out. The possibility of reusing an already existing
JT, in order to obtain the new one regarding only the modifications in the
network has received only little attention in the literature. In this paper we
present a method for incremental compilation of a Bayesian network, following
the classical scheme in which triangulation plays the key role. In order to
perform incremental compilation we propose to recompile only those parts of the
JT which can have been affected by the networks modifications. To do so, we
exploit the technique OF maximal prime subgraph decomposition in determining
the minimal subgraph(s) that have to be recompiled, and thereby the minimal
subtree(s) of the JT that should be replaced by new subtree(s).We focus on
structural modifications : addition and deletion of links and variables.
