hello all,
in my work i use Bayesian networks to simulate the outcome of some events
based on prior events. By simulate i mean i find out the probabilities of
the outcomes based on the inputs and then choose randomly one of those
outputs. I submitted this to UAI, and got in my review the comment that
Bayesian network troubleshooting/diagnosis systems could be used
predictively by injecting boundary conditions and randomly generating
outputs, and that Monte Carlo diagnostic methods use simulation to achieve
abduction. Can anyone point me to some reference on these specific points?
thanks in advance for your time and attention.
-Jeff
-- Jeferson Valadares Cofounder & Creative Director/Jynx Playware ___________________________________________ http://www.jynx.com.br +55.81.3272-4700x4729/Recife/Brasil
This archive was generated by hypermail 2b29 : Mon Jun 03 2002 - 09:22:06 PDT