Actually, because fuzzy logic is very good at
reconciling differences like this, you might want to
check out the following sites:
http://www.cs.cmu.edu/Groups/AI/html/faqs/ai/fuzzy/part1/faq-doc-2.html
http://ai.iit.nrc.ca/IR_public/fuzzy/fuzzyJToolkit.html
(based on jess)
-Michael McConnell
--- Chad Loder <[EMAIL PROTECTED]> wrote:
> Hello. I'm working on ways to do something like
> this with Jess:
>
> 1) given some evidence, collect all possible
> diagnoses
>
> 2) once all diagnoses have been asserted, find
> any conflicting diagnoses (basically I want to
> do something like:
>
> "If there exists a diagnosis-fact X and a
> distinct
> diagnosis-fact Y s.t. X and Y agree on some
> particulars
> but disagree on other particulars, then
> assert(needs-resolution (X Y))"
>
> 3) and then later on down the road, use some sort of
> merge-logic or graph partitioning to merge
> compatible
> diagnoses and resolve conflicting diagnoses
>
> Is stage (2) possible within Jess? I see in
> the documentation that the (exists) CE does not let
> you bind the triggering fact -- from a performance
> point-of-view, I understand why that restriction
> must exist.
>
> So my question is, what's the best way to do this?
> I suppose I could add a JessListener and then build
> a graph of the relevant facts (where I connect
> edge(X,Y)
> iff X and Y are compatible).
>
> Is there a more elegant approach to step 2? Or
> indeed,
> if a more elegant approach exists to the whole
> problem,
> please let me know.
>
> The restrictions are, it must be based on or in
> Jess,
> not extremely computationally expensive, and
> implementable
> in Java by someone who's not a genius (aka myself).
>
> Thanks,
> Chad Loder
>
>
>
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