Bayesian Networks

Preface

Applications of Bayesian networks have multiplied in recent years, spanning

such different topics as systems biology, economics, social sciences and medical

informatics. Different aspects and properties of this class of models are crucial

in each field: the possibility of learning causal effects from observational data

in social sciences, where collecting experimental data is often not possible; the

intuitive graphical representation, which provides a qualitative understanding

of pathways in biological sciences; the ability to construct complex hierarchi-

cal models for phenomena that involve many interrelated components, using

the most appropriate ...