Hi, I am also interested in this question. Bayes net is a perfect model for information processing. Its nodes and links do the reasoning with the Bayes’s theorem when more information comes in. It ensures that the information flowing in Bayes net keeps balance. So intuitively, Bayes net is an ideal 'communication net' for information exchanging. Thus, its nodes can be a 'communication channel'.
As for the uncertainty evaluation and entropy, entropy is the diversity evaluation. Does the diversity equal to uncertainty? My idea about the question is to evaluate the entropy in a range of time,like from Time t1 to t2, If there are no change of entropy in this distance(t1,t2) when more information (data) enters in (t1,t2). We can see there are no chance to improve the certainty of nodes. This is just my rough idea. Welcome comments! Regards! Yifeng - -----Original Message----- From: Julian Russell [mailto:[EMAIL PROTECTED] Sent: 2003年9月23日 20:53 To: [EMAIL PROTECTED] Subject: [UAI] Entropy of a Node in a Bayes Net? Dear list members, Does it make sense to calculate the entropy of a node in a Bayes net by using Shannons communication entropy equation? Can a node be considered a 'communication channel' for this purpose? Following on from this would it be reasonable to measure the change in entropy as more data is added to the decision model, thereby decreasing the uncertainty/risk by defining the node with more certainty, as measured by the progressively decreasing entropy? Regards, JR
