Reasoning in Bayesian nets

• Probabilities in links obey standard conditional probability axioms.
• Therefore follow links in reaching hypothesis and update beliefs accordingly.
• A few broad classes of algorithms have bee used to help with this:
  • Pearls's message passing method.
  • Clique triangulation.
  • Stochastic methods.
  • Basically they all take advantage of clusters in the network and use their limits on the influence to constrain the search through net.
  • They also ensure that probabilities are updated correctly.
• Since information is local information can be readily added and deleted with minimum effect on the whole network. ONLY affected nodes need updating.