On Sun, Sep 21, 2008 at 10:43 PM, Abram Demski <[EMAIL PROTECTED]>wrote:
> The calculation in which I sum up a bunch of pairs is equivalent to > doing NARS induction + abduction with a final big revision at the end > to combine all the accumulated evidence. But, like I said, I need to > provide a more explicit justification of that calculation... As an example inference, consider Ben is an author of a book on AGI <tv1> This dude is an author of a book on AGI <tv2> |- This dude is Ben <tv3> versus Ben is odd <tv1> This dude is odd <tv2> |- This dude is Ben <tv4> (Here each of the English statements is a shorthand for a logical relationship that in the AI systems in question is expressed in a formal structure; and the notations like <tv1> indicate uncertain truth values attached to logical relationships, In both NARS and PLN, uncertain truth values have multiple components, including a "strength" value that denotes a frequency, and other values denoting confidence measures. However, the semantics of the strength values in NARS and PLN are not identical.) Doing these two inferences in NARS you will get tv3.strength = tv4.strength whereas in PLN you will not, you will get tv3.strength >> tv4.strength The difference between the two inference results in the PLN case results from the fact that P(author of book on AGI) << P(odd) and the fact that PLN uses Bayes rule as part of its approach to these inferences. So, the question is, in your probabilistic variant of NARS, do you get tv3.strength = tv4.strength in this case, and if so, why? thx ben ------------------------------------------- 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=114414975-3c8e69 Powered by Listbox: http://www.listbox.com
