Re: abstract vs concrete concepts. upper ontolologies

Milton

knowledge representation is a vast field, and I am glad to see you are now
applying yourself to expound it to its full extent
we look forward be reading your novel contributions to the field,

At this time, the work that I am sharing consist of capturing the knowledge
representation domain *and its subdomains
for the purpose of supporting the development of AI agents,  *AI KR  vs
other types of KR
starting from creating a set of vocabularies, which is an ambitious enough
scope

The universe of discourse is vast, agents are built to carry out specific
tasks,


P


On Fri, Jun 27, 2025 at 10:46 PM Milton Ponson <rwiciamsd@gmail.com> wrote:

> If we take into consideration the fact that philosophy is characterized
> generally by having five branches, that is (1) metaphysics, (2)
> epistemology,  (3) logic, (4) ethics and (5) aesthetics we can conclude
> that the abstract concepts can be categorized accordingly.
>
> For completeness sake we can add philosophy of science, which roughly said
> looks at how methodologies evolve and shape rational thinking and empirical
> science.
>
> Logic, linguistics and mathematics form the core to capture abstract
> concepts in formal systems that lend themselves for computation, as is
> obvious in LLMs.
>
> But philosophy for practical purposes is a better organizing instrument
> for knowledge representation,  exactly because it includes but is not
> identical to epistemology.
>
> And because language is the instrument of communication for philosophy,
> we are back to my premise to use semiotics,  symbol sets, pictograms,
> (petro)glyphs and alphabets as the basis for abstraction.
>
> Because empirical science generates (spectral) data, these must described
> as well both quantitatively and qualitatively.
>
> And because we are trying to create open, inclusive, accountable,
> explainable,  trustworthy,  ethical and safe artificial intelligence that
> is life-centric (not human-centric, but safe for all life on Earth), the
> first four mentioned branches of philosophy form the basis for organizing
> knowledge and its representation.
>
> Of these four the first three have already been studied in extenso, it is
> now only recently that ethics has joined the fray.
>
> Again, I am working on producing several articles on both the organizing
> instruments and formal systems for (abstract) knowledge representation.
>
> I hope I have clarified my approach, I am a Godelian mathematician, which
> means I acknowledge that universal theories of everything that are
> consistent and complete do not exist, but we can construct formal systems
> that can satisfy some requirements we may have for explaining empirical
> data, and allow computation.
>
> And since metaphysics,  epistemology,  logic and ethics cover pretty much
> everything we want to capture in knowledge representation,  this should
> suffice for all fields of human activity and Science, Technology,
> Engineering and Mathematics in which we want to utilize artificial
> intelligence.
>
> Milton Ponson
> Rainbow Warriors Core Foundation
> CIAMSD Institute-ICT4D Program
> +2977459312
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
>
> On Fri, Jun 27, 2025, 09:36 Paola Di Maio <paola.dimaio@gmail.com> wrote:
>
>>
>> To understand why, in trying to capture the Knowledge Representation
>> domain, which can be so elusive
>> we start with upper/top level ontologies,
>>
>> There is a distinction between abstract vs concrete concepts
>>
>> The majority of words in English *check the other languages? *estimated
>> around 70 percent, refer to abstract concepts
>> These cannot be represented visually
>> Yet, these abstract concepts convey essential meaning and semantics for
>> concrete terms
>> abstraction is essential to intelligent reasoning
>>
>> Upper Ontologies represent abstract categories require to add semantic
>> dimensions to concrete terms and concepts
>> PDM
>>
>>
>> 1. Existence and Reality
>>
>> being / nonbeing
>>
>> existence / inexistence
>>
>> possibility / necessity
>>
>> actuality / potentiality
>>
>> ________________________________
>>
>> 2. Time
>>
>> duration
>>
>> moment / instant
>>
>> past / present / future
>>
>> frequency
>>
>> continuity / interruption
>>
>> ________________________________
>>
>> 3. Space and Place
>>
>> position / location
>>
>> distance / proximity
>>
>> direction
>>
>> extent / limit
>>
>> movement through space
>>
>> ________________________________
>>
>> 4. Quantity and Measurement
>>
>> number
>>
>> magnitude
>>
>> degree
>>
>> proportion
>>
>> comparison
>>
>