On 1/29/07, Ben Goertzel <[EMAIL PROTECTED]> wrote:

Pei Wang's uncertain logic is **not** probabilistic, though it uses
frequency calculations
IMO Pei's logic has some strong points, especially that it unifies fuzzy and
probabilistic truth values into one pair of values.  I think in Pei's logic
the frequency f is indeed a probability.  In your logic, do you treat
fuzziness and probabilities separately?

We have our own probabilistic logic theory called Probabilistic Logic
Networks (PLN), which will be described in a book to be released
toward the end of this year or the start of 2008.

Looking forward to your book!

The differences btween NARS and PLN are too numerous for an email,
but among them are

-- PLN is based on a probabilistic semantics whereas NARS uses a
different semantics
-- PLN uses a combination of term logic and predicate logic whereas
NARS is more strictly a term logic approach

These foundational differences lead to a large number of more
specific technical differences, not surprisingly.

For instance, the NARS inference formulas only involve the uncertain
truth values of relationships, whereas PLN's involve the uncertain
truth values of both relationships and terms.   Relatedly, the PLN
induction and abduction formulas utilize Bayes rule whereas the NARS
induction and abduction formulas do not...


It seems that a term cannot be uncertain.  For example, "women have long
hair" may be associated with a probability, but "women" as a term does not
seem to be probabilistic.  I wonder why you say terms can have truth values?

My question is:  If I provide a set of facts/rules associated with Pei-style
uncertain values (2 numbers), would Novamente find it useful?  Is it easy to
convert that into NM's PLN?

YKY

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