expert systems are unable to apply the knowledge they contain. So for
example, an expert system in geological formations is not actually able to
drill oil wells ... it simply can provide yes/no answers to questions, or
provide advice (e.g. "oil wells near the edges of granite domes are often
productive")
Thus, an expert system in learning could maybe give advice to teachers
about teaching, but that would not make it itself capable of learning ...
the encoded knowledge is too abstract. ("writing an essay after reading a
book often leads to learning")
--linas
On Fri, Mar 24, 2017 at 9:43 AM, Michael S <[email protected]> wrote:
> Hi sorry to reply to older thread, but could one make an expert system
> whose domain *is* learning itself (supervised or unsupervised)? In
> theory, I mean.
>
> Like, such an expert system could be filled with knowledge about learning
> and epistemology, and its inference engine would be taught rules about how
> to learn that are very domain-general. Then perhaps, once you've laid the
> framework by teaching the system how to learn in a formal logical way as an
> expert system (as opposed to more "hidden" and not readily editable machine
> learning algorithms), I wonder if you could use that "learning expert" to
> learn other things better. I wonder if an expert system like this (or any
> other) could be used by a machine learning supersystem, or another expert
> supersystem--these would be higher-level intelligences then maybe.
>
> I've personally been interested in approaching AGI from the formal logical
> perspective instead of the machine learning probabilistic perspective, so I
> thought this was interesting post.
>
> On Wednesday, March 8, 2017 at 10:05:13 PM UTC-5, Ben Goertzel wrote:
>
>> On Thu, Mar 9, 2017 at 2:03 AM, Andrei Suiu <[email protected]> wrote:
>> >
>> > At the first view it looks like AtomSpace is basically a Knowledge
>> Base, and
>> > the MindAgents are Inference Engines, that makes OpenCOG look like an
>> Expert
>> > System
>>
>>
>> No.
>>
>> Most MindAgents are not inference engines -- e.g. calling clustering,
>> or ECAN (importance spreading), an "inference engine" is way too much
>> of a stretch
>>
>> Further, "expert systems" typically have their knowledge bases filled
>> via curated or hand-coded knowledge, not via knowledge obtained by
>> learning
>>
>> Of course, if you stretch the definition far enough you can convince
>> yourself a human baby is an "expert system" (it contains some expert
>> knowledge about drinking milk from its mommy, in its knowledge base),
>> but ... well ...
>>
>>
>>
>> --
>> Ben Goertzel, PhD
>> http://goertzel.org
>>
>> “Our first mothers and fathers … were endowed with intelligence; they
>> saw and instantly they could see far … they succeeded in knowing all
>> that there is in the world. When they looked, instantly they saw all
>> around them, and they contemplated in turn the arch of heaven and the
>> round face of the earth. … Great was their wisdom …. They were able to
>> know all....
>>
>> But the Creator and the Maker did not hear this with pleasure. … ‘Are
>> they not by nature simple creatures of our making? Must they also be
>> gods? … What if they do not reproduce and multiply?’
>>
>> Then the Heart of Heaven blew mist into their eyes, which clouded
>> their sight as when a mirror is breathed upon. Their eyes were covered
>> and they could see only what was close, only that was clear to them.”
>>
>> — Popol Vuh (holy book of the ancient Mayas)
>>
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