I do have a design that handles uncertainty in axiomatic reasoning, but
it is not in the form of a Bayesian net. Furthermore, in my design
"implication" and "causation" are fundamentally different, though
closely related.
If everything goes as planned, I should have that design implemented in
Eli,
In the PTL inference framework we use in Novamente, we use a two-valued
truth value inspired by Pei Wang's NARS (which is quite different from PTL
in many other ways)
-- One component is a probability
-- Another component represents the weight of evidence underlying the
computation of the p
I haven't found anything to recommend, and I've been playing with
similar things for a couple years. It would be a great topic for a
paper (or two).
j. andrew rogers
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Have any of you seen a paper out there that integrates uncertainty about the
results of deterministic computations into Bayesian networks? E.g., being
unsure whether 2 + 2 = 4 or 2 + 2 = 5. In particular I'm wondering whether
anyone's tried to integrate axiomatic proof systems into causal netw