On 8/6/08, Jim Bromer <[EMAIL PROTECTED]> wrote: > > You made some remarks, (I did not keep a record of them), that sounds > similar to some of the problems of conceptual complexity (or > complicatedness) that I am interested in. Can you describe something > of what you are working on in a little more detail in a way that > should make it easy for me to understand? To start with, what does > "distribute probabilities over fuzziness," mean exactly. Are you > trying to use first order Bayes nets to examine different distribution > patterns? Does first order Bayes nets refer to something similar to > the inductive logical probability that you titled this thread after?
I'm writing a paper about my probabilistic-fuzzy logic that should be fairly easy to understand. But I got stuck on the fuzzy concept problem as you can see. To "distribute probabilities over fuzziness" means: each concept has a fuzzy value, Z, in [0,1]. For example, the "chairness" of a certain chair may be 0.7. I can add probabilities on top of this: the mean of Z would be at 0.7, with a bell-curve kind of distribution. So I use 2 numbers, the mean and the variance. That allows me to approximate an interval Z value such as [0.6,0.8]. Probabilistic ILP can be performed on this KR structure (analogous to ILP on FOL). YKY ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=108809214-a0d121 Powered by Listbox: http://www.listbox.com
