Re: Bayesian Networks and Belief Functions

[Judea Pearl]

Kathy,
You say:
     No matter what prior probability we put on Q, the marginal probability
        of R in any probability model would lie between 0.8 and 0.9.
        One can "explain" the phenomenon (i.e. Bel(R)=0.72)
        by saying that there is only a 0.72 chance that "the 
        evidence would prove R," but I was never able to come up 
       with a way to argue this convincingly to a subject matter expert. 

This was one of my problems too, but watch how sensible it
sounds when translated into the scheduling example I gave:

     "No matter what prior probability we put on Q, the probability
     that I will be assigned to teach class R would lie 
     between 0.8 and 0.9.
     Still, the probability that I WILL BE FORCED to teach
     class R, for lack of an alternative consistent
     assignment, is 0.72."

Do you find any difficulty explaining this to 
a subject matter expert?

============Judea