A somewhat revised version of my paper is at: http://www.geocities.com/genericai/AGI-ch4-logic-9Sep2008.pdf (sorry it is now a book chapter and the bookmarks are lost when extracting)
On Tue, Sep 2, 2008 at 7:05 PM, Pei Wang <[EMAIL PROTECTED]> wrote: >> >> I intend to use NARS confidence in a way compatible with >> probability... > I'm pretty sure it won't, as I argued in several publications, such as > http://nars.wang.googlepages.com/wang.confidence.pdf and the book. I understood your argument about defining the confidence c, and agree with it. But I don't see why c cannot be used together with f (as *traditional* probability). > In summary, I don't think it is a good idea to mix B, P, and Z. As Ben > said, the key is semantics, that is, what is measured by your truth > values. I prefer a unified treatment than a hybrid, because the former > is semantically consistent, while the later isn't. My logic actually does *not* mix B, P, and Z. They are kept orthogonal, and so the semantics can be very simple. Your approach mixes fuzziness with probability which can result in ambiguity in some everyday examples: eg, John tries to find a 0.9 pretty girl (degree) vs Mary is 0.9 likely to be pretty (probability). The difference is real, but subtle, and I agree that you can mix them but you must always acknowledge that the measure is mixed. Maybe you've mistaken what I'm trying to do, 'cause my theory should not be semantically confusing... 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=111637683-c8fa51 Powered by Listbox: http://www.listbox.com
