What
is an Expert System
(Last updated 11 March 2007)
The term Artificial
Intelligence (AI) was first used at a conference at Dartmouth
College in 1958. Since that
time, AI has come to mean many things; robotics, neural networks, rulebased
systems and knowledgebased systems. KBSC deals mostly with rulebased systems
in the business world where they are sometimes referred to as Business Rule
Management Systems, BRMS.
A BRMS is normally one or more sets of ifthenelse rules managed by a
nonmonotonic inference engine that is Turing Complete.
The Universal
Turing Machine as well as the ChurchTuring Thesis
is also discussed on Wikipedia. An even more enlightening look at ChurchTuring
is kept at Stanford and points out many of the “misquotes” that have been
attributed to their thesis in the past in many different disciplines. Alan Turing,
one of the leading mathematicians of his day, greatly contributed to
breaking the German Nazi Enigma cryptology machine during WW II. Dr. Charles Forgy,
inventor of the Rete Algorithm, Rete 2 Algorithm and the Rete III
extensions to Rete 2 Algorithm, had this to say about Turing, Church and Gödel:
“The
ChurchTuring thesis basically says that all computing machines beyond a
certain (surprisingly low) level of complexity are equally powerful.
That is, anything that can be computed by one computing machine can be
computed by all computing machines. The Turing Machine is one
example; Church’s lambda calculus is another. To show that a new
model is equivalent to the others only requires that one show the new model
can simulate one of the old models. Regarding production systems, it
is trivially easy to write rules to simulate a Turing Machine.
There
is another result, the Gödel Incompleteness Theorem that is often mentioned
in relation to intelligence. It says that every formal system of a
certain power (basically powerful enough to model itself) is either
incomplete or inconsistent. Some people claim that this is evidence
that machines can never be as intelligent as people. After all,
people can create new axioms to create ever more powerful logical systems
when they need to. The flaw in this argument, in my opinion, is that
the argument focuses on the “incomplete” part of the theorem while ignoring
the “inconsistent” part. If someone can show me a person who has not
a single inconsistency in his world model, then I might grant that people
are not subject to the incompleteness theorem.”
Normally, the rules are gathered in an
intelligent manner, called Knowledge Extraction or Knowledge Acquisition,
by a Knowledge Engineer (KE) and implemented by a Rule Engineer (RE) into
the engine along with any other computer programs necessary for the rules
to function. In a true BRMS
the rule architecture may be designed by the KE but the rules could be
entered by a Business Analyst.
While nonmonotonic is a term used to describe the actions of an inference
engine wherein the ifthenelse clauses are examined over and over, a more
proper definition was offered by Dr. Charles Forgy
et al: “A logic system is monotonic if the truth of a proposition does not
change when new information (axioms) are added to the system. In contrast,
a logic is nonmonotonic if the truth of a proposition may change when new
information (axioms) is added to or old information is deleted from the
system.”
There is a rather good link on First
Order Propositional Logic (FOPL) at CMU. As you can see, I offer very little
in the way of theoretical studies but rather I am an implementer (KE) as
well as maintaining a small research lab where we gather tools, analyze
those tools, write articles on those tools and run benchmarks. Some benchmarks may be found at the
following links:
Expert
System Links
we specialize in Intelligent
Business Rule Management Systems (iBRMS)  the same thing that used to be
called rulebased systems by the AI companies.
