Decision-theoretic specification of credal networks: A unified language for uncertain modeling with sets of Bayesian networks

Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Credal nets appear to be powerful means to represent and deal with many important and challenging problems in uncertain reasoning. We give examples to show that some of these problems can only be modeled by credal nets called non-separately specified. These, however, are still missing a graphical representation language and updating algorithms. The situation is quite the opposite with separately specified credal nets, which have been the subject of much study and algorithmic development. This paper gives two major contributions. First, it delivers a new graphical language to formulate any type of credal network, both separately and non-separately specified. Second, it shows that any non-separately specified net represented with the new language can be easily transformed into an equivalent separately specified net, defined over a larger do...

• Type: Journal
• Year: 2008
• Where: IJAR
• Authors: Alessandro Antonucci, Marco Zaffalon
• Keywords: Bayesian Nets, Credal Nets, Credal Network, IJAR 2008