Re: [ontolog-forum] New Postulate formulation on AI KR

All:

The statement:

"Interdisciplinarity is fundamental to problem solving in most domains, and
applied science and engineering are concerned primarily with problem
solving, rather than purely theoretical formulations"

Appears to relate directly to General Systems Theory.  See:

https://www.researchgate.net/publication/323387658_A_General_Systems_Context_for_Structural_Modeling

https://www.panarchy.org/boulding/systems.1956.html

The proper alignment of natural language and formal language may be
addressed in a range of view points.

Some issues and ideas are outlined at:

https://www.researchgate.net/publication/324138184_System_Concepts_and_Theories

Take care, be good to yourself and have fun,

Joe






On Mon, Aug 26, 2019 at 1:42 AM Paola Di Maio <paola.dimaio@gmail.com>
wrote:

> Thank you Alex
>
> variations/elaborations  welcome (Vx)
>
> There is a problem with math KR tho - which has been discussed forever
> I ll summarise it briefly hoping to put things to rest:
>
> Interdisciplinarity is fundamental to problem solving in most domains, and
> applied science and engineering are concerned primarily with problem
> solving, rather than purely theoretical formulations
>
> Interdisciplinarity means not everyone uses maths (  apparently even
> mathematicians sometimes use different types of maths) Most domain experts
> are not mathematicians
>
> Therefore, maths, like ml should also be translatable/mappable to to plain
> natural language, even better to some diagrammatic notation  or logical
> language that reproduces the logical schema ideally, problems and solutions
> should be represented in a multiplicity of ways
>
> This particular postulate - luckily I dont wake up early morning to
> postulate very often - has been prompted but the need to fill a gap between
> symbolic an subsymbolic KR as per the posts, and having a citable reference
> I am sure it can be refined further
> PDM
>
>
>
> On Mon, Aug 26, 2019 at 4:29 PM Alex Shkotin <alex.shkotin@gmail.com>
> wrote:
>
>> Paola,
>>
>> I keep in mind a variation of your postulate:
>> Any algorithm (including MLA) has math representation.
>>
>> This is all that we have been talking about since Leibniz: math
>> knowledge representation:-)
>> The problem is that computer programs and DBs are not mathematical structures
>> but they work:-)
>>
>> Alex
>>
>> пн, 26 авг. 2019 г. в 05:27, Paola Di Maio <paola.dimaio@gmail.com>:
>>
>>> Since posting  discussions about bridging the gap between symbolic and
>>> subsymbolic, (see related posts) I have formulated a simple postulate, and
>>> assigned a DOI so that anone following up on these discussions can cite the
>>> contribution accordingly. I ll be happy to review the postulate with
>>> comments and suggestions if any
>>>
>>> To support AI explainability, learnability,verifiability and
>>> reproducibility, it is postulated that
>>> for each MLA *machine learning algorithm,
>>> there should correspond a natural language expression or other type of
>>> symbolic knowledge representation
>>>
>>> https://doi.org/10.6084/m9.figshare.9730268.v2
>>>
>>> https://figshare.com/articles/A_New_Postulate_for_Knowledge_Representation_in_AI/9730268
>>>
>>>
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-- 
Joe Simpson
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