ah I see, thank you for explaining :)
On Thursday, March 23, 2017 at 10:03:53 PM UTC-4, linas wrote:
>
> 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]
> <javascript:>> 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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