Figure 4

Comparing a Bayesian Network and logic or event tree. (a) This is an elementary BBN representing a very simple volcanological model to infer the probability of eruption resulting from magmatic unrest. Unrest (shaded grey) cannot be observed directly, and must be inferred from observations (e.g. seismicity and SO₂ emission, shaded blue). The query node (shaded pink) is the outcome of interest - eruption. For a generic Bayesian Network B = {X,Y,U}; X represents the set of unobserved or hidden states, Y the set of observable states, and U the set of arcs or directed links between nodes. Arrows indicate direction of causality or influence. For the simple case where nodes are assigned discrete states, node relationships are described by conditional probability tables (CPTs). States must be mutually exclusive and exhaustive. (b) presents an equivalent logic tree representation of the basic BBN in (a). For simplicity two alternative states are shown for each node.