Ralf Finne <Ralf.Finne <at> syh.fi> writes:>
> Hi R-users
> Is there any functions in R that can implement "expert systems"?
> The aim of an expert system is to produce a probable diagnosis
> for a patient with certain symptoms.
> In the classical expert system a mumber of "experts" are asked to
make
> "statements" on the probabilities for different diseases when a
> combination of systems would appear. One typical "expert
system"
> uses Fuzzy Logic to suggest the diagnosis.
>
> In more modern systems one tends to make the system self learning
> to improve the system.
>
What you are describing here is just one of several ways to realize an
"expert
systems". And the question is also what kind of technique you would like to
implement such a system in, e.g., rule-based, fuzzy sets, (Bayesian) networks,
constraints, case bases, etc.
The closest R may come to expert system techniques is through Weka in the RWeka
package (I should also mention 'deal' for graphical networks). R as
statistical
software focuses more on the learning aspect, not on explicitly representing
'knowledge' in whatever form.
There are commercial and free "expert system shells" one could
utilize. CLIPS
<http://clipsrules.sourceforge.net/> is a bit old-fashioned, but could
easily be
integrated with R; JESS <http://www.jessrules.com/> being another one.
Also Prolog systems (especially if they include CSP solvers) such as BProlog or
SWI Prolog are free and could be combined (at least through file or pipe
transfer) with R to generate complete applications.
Regards, Hans Werner Borchers
> Hoping for comments
> Ralf Finne
> Swenska yrkesh?gskolan
> Vasa Finland
>
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