CORRECTD For each bubble, a container for KR terms

oops ---  the spellchecker converted the work folks into fools,   oh my,
thats machine for you
Resending the Corrected message below

On Sun, Nov 23, 2025 at 1:00 PM Paola Di Maio <paoladimaio10@gmail.com>
wrote:

> Tyson,  thanks for your inquiry
>
> Your question shows understanding the big picture and a propensity of
> integral, systems thinking
> and functional decomposition, which I can relate to
>
> Your approach to distinguishing different levels of analysis can be
> useful,
>
> This is also my first post to the S AGENT community, so I ll try to make
> it sound like a position statement
> I am jumping at the chance to evangelize about KR, once more
>
> For many of us, This has been/still is a steep learning curve
>
> At the top of the hierarchy is LOGOS   *logic
>   --------Lookup different types of logic/logical formalisms/logical
> languages
>
> -----------Different forms of logic may be suited for different kinds of
> reasoning mechanisms and different languages may be suited for
> better representing logic and reasoning, depending on the use case, the
> environment , the platform etc
>
> In the last decade or so, we have seen a wave of machine learning AI
> driving scientific and technological progress
> I found the notion of   'fragmented logic'  in AI systems problematic
> i discuss the concern here in our first report
>
> https://www.w3.org/community/aikr/wiki/images/7/7b/AI_KR_FIRST_REPORT_PUBLISHED_VERSION.pdf
>
> More recently we are focusing on LLM *forget the rest of AI for a moment
> (too big a topic)
>
> Knowledge Representation *in itself a vast field that developed
> alongside computation in the last century (among other fields to which KR
> is relevant)
>
> KR that uses NL
>
> can help humans stay in the loop, by supporting natural
> language understanding *NLU
> thus enabling experts with multidisciplinary backgrounds to share knowledge
>
> Now we are doing LLM evaluations that require domain experts to validate
> the outcomes of LLMs (across a number of fields)
> Fools  Folks do not speak machine language, nor use maths to communicate
>
> *I*intelligent reasoning and human understanding of what constitutes
> intelligent reasoning,  are represented by logic, which is expressed with
> either human natural languages and/or with formal languages, Mathematics is
> one such language. Description Logic DL is another
>
> While structural engineering uses calculus , architects use drawings to
> convey shapes, spatial concepts, where windows and doors are place, their
> size etc.  KR embraces all of these formalisms, the designer.engineer
> selects the most appropriate ones according to their goals, methods,
> resources.
>
> Here in this CG *AI KR CG we have aimed so far to chart the field of
> knowledge representation so that when we try
> to understand LLM outputs we have a compass for orientation rooted in
> Logic which can be represented and interacted with using  Natural Language
>
> Referencing some very old conversations if you can find a way of querying
> Ontology archives before it migrated to Google Group
> http://ontolog.cim3.net/forum/ontolog-forum/2007-03/msg00150.html
>
> A lot of interesting conversations there about KR *where I learned the
> ropes
>
> In the link below some notes showing a graphical representation of how a
> human problem solver would represent knowledge about the engine
> not starting
>
> https://docs.google.com/document/d/1dKVibyqHJ3Qoy7WrqPUYi6iwZN94T5puJrgKEJFYV1I/edit?usp=sharing
>
> I am surprised how good translation of notations works across formalism
> These days we can translate any formalism into any other formalism
> including hieroglyphs!!
>
> Is mathematics a KR language ? Yes!
> Is it a natural language that humans and LLMs communicate with?  No!
>
>
> So much more to say!  So now we are focusing on publishing a few
> vocabularies and schemas that represent
> the KR domain,  to help us navigate the evolving field of AI and support
> our LLM  evaluations
>
> I look forward to be learning more about the S AGENT COMM is dong and how
> can KR contribute to it
> and if ou have anthing relevant to contribute to our next report to be
> published soon *a shared concern, or a shared solution
> please lets crosslink
>
> Best regards
>
> Paola Di Maio
>
>
> On Sat, Nov 22, 2025 at 12:25 PM 陳信屹 <tyson@slashlife.ai> wrote:
>
>> Thanks again to all of you for the very insightful sharing.
>>
>> As someone who is newly entering the KR domain, I have been trying to
>> understand the overall landscape by organizing the concepts using the
>> following layered architecture.
>>
>> ```
>> [L4] Semantic Execution Layer (our work: semantic agent communication CG)
>>     └─ OS-level execution, agent sandboxing, DID/VC identities,
>>        semantic ledger, cross-agent message schemas
>>
>> [L3] Semantic Behavior Layer (our work: semantic agent communication CG)
>>     └─ Contracts, capabilities, delegation structures,
>>        execution-context models
>>
>> [L2] Semantic Positioning (Milton)
>>     └─ Conceptual placement of KR between
>>        language-sensitive context and application-level behavior
>>
>> [L1] Semantic Materials (Paola)
>>     └─ Vocabulary sets, definitions, classifications,
>>        semantic maps, knowledge-representation corpora
>>
>> [L0] Semantic Atoms (Daniel)
>>     └─ Character-level units combining form, meaning,
>>        procedural RPN programs, and embedding space
>> ```
>>
>> My intention is simply to understand how different lines of work relate
>> along the spectrum from semantic materials and definitions (L0–L1), to
>> conceptual positioning (L2), to behavior-level structures (L3), and finally
>> to execution frameworks (L4) .
>>
>> If this mapping misrepresents anything, I would be grateful for your
>> guidance.
>> Thank you again for the discussion and for helping me understand the
>> field more clearly.
>> Paola Di Maio <paoladimaio10@gmail.com> 於 2025年11月20日 週四 上午10:37寫道：
>>
>>>
>>> Milton and others
>>> I am glad there is interest in KR and the work being done by this CG,
>>>
>>> Please feel free to share your work, you do not need anybody's
>>> permission to draw diagrams, write papers or present your
>>> evaluations *provided these are related to the work being done
>>>
>>> It is quite difficult to get people to read our work, this is why we
>>> must validate our own
>>> work externally and try to publish it *better still if it has some
>>> evaluation and validation built in
>>>
>>> I am now training  agents *as per the talk on KRL and have become very
>>> absorbed, so I  need to focus
>>> my attention where it is needed
>>>
>>> Next steps for me
>>> - try to wrap up some vocabs (possibly a subset) the open them up for
>>> evaluation and consultation
>>> - find out if and how to move forward toward a specification
>>> - training Agents to  support this work.
>>>
>>> CG participants with the required competences and resources please get
>>> in touch to help with the plan
>>>  we may cook something together
>>> and share the results with this list
>>>
>>> Look forward to be reading your papers or listening to your talks on
>>> KR,, Milton and everyone, whether it is literature reviews, state of the
>>> art reports or new advances
>>>
>>> Best
>>> Paola
>>>
>>>
>>> On Thu, Nov 20, 2025 at 2:25 AM Milton Ponson <rwiciamsd@gmail.com>
>>> wrote:
>>>
>>>> Maybe it is necessary to explain my point of view in plain language.
>>>>
>>>> Knowledge representation is "the man in the middle" between knowledge
>>>> and application.
>>>>
>>>> Both ends define the contexts for the man in the middle, and both ends
>>>> are determined by specific domains of knowledge or application.
>>>>
>>>> We can create general frameworks on both sides of the man in the middle.
>>>>
>>>> On the left hand side natural language context sensitive and right hand
>>>> side computationally application specific.
>>>>
>>>> Maybe we should redraw the bubbles graph to reflect this.
>>>>
>>>> Milton Ponson
>>>> Rainbow Warriors Core Foundation
>>>> CIAMSD Institute-ICT4D Program
>>>> +2977459312
>>>> PO Box 1154, Oranjestad
>>>> Aruba, Dutch Caribbean
>>>>
>>>> On Wed, Nov 19, 2025, 12:12 Paola Di Maio <paola.dimaio@gmail.com>
>>>> wrote:
>>>>
>>>>>
>>>>> Just to remind newcomers, and participants who may have not followed
>>>>> the work being done in detail
>>>>> or may have lost sight of the mission *admittedly we have had wide
>>>>> ranging conversations on this list
>>>>>
>>>>>  that over the years, hundreds of terms representing the KR domain
>>>>> have been
>>>>> collected, refined, and evaluated for inclusion from the corpus
>>>>>
>>>>> Not just academic literature, but lecture notes, from use cases and
>>>>> technical documents in use.
>>>>> Some of these vocabs are being peer reviewed, but still far from being
>>>>> final!
>>>>>
>>>>> So for each bubble in the diagram  *note I have produced a new version
>>>>> with links to the vocabulaires, but at this moment these are not shared
>>>>> resources yet
>>>>>
>>>>> [image: AI KR VOCABS NOV 2025(1).jpg]
>>>>>
>>>>>
>>>>>  providing an overview of the conceptual spaces in KR, there is
>>>>> vocabulary capturing hundreds of terms and concepts extracted from the
>>>>> KR corpus.   Would not say this is quite 'core vocabulary for KR yet *
>>>>> because it needs refinement
>>>>> We have over 1400 unique terms from one category alone
>>>>>
>>>>> I am confident that it is the most extensive map of the KR domain
>>>>> *and it is becoming difficult to handle
>>>>>
>>>>> For each vocabulary, now I have different versions. Some have
>>>>> definitions *a version of which is being done by Chris Harding
>>>>>   Some have categories attached to them.
>>>>> I am not ready to share them publicly,  but I have managed to publish
>>>>> one set *KRL in the proceedings of the DCMI conference
>>>>> *should be open access soon  together with the evaluation methodology
>>>>>
>>>>> I have shared the vocabulary drafts on this list with CG participants
>>>>> who expressed an interest
>>>>> At this stage, and not until we have a better understanding of how to
>>>>> handle this material, I have restricted access
>>>>>
>>>>> It s hundreds of hours of very interesting work
>>>>> In the link below, shared on a post to this list on 22 October here, I
>>>>> provide the rationale and pointer to the KRL vocab *corresponding to the
>>>>> bubble on the right in the diagram
>>>>>
>>>>> *pre recorded talk here
>>>>>
>>>>> https://drive.google.com/file/d/1ZXGxsFXvnTXm_knYXbax0I2HdqfWuNWK/view?usp=sharing
>>>>>
>>>>> I do not expect that participants read all emails but that s the only
>>>>> way to keep up sometimes
>>>>>
>>>>> This is why I plan a report shortly summarizing all the resources
>>>>> produced to date, and of course, welcome evaluation and refinement
>>>>>
>>>>> PDM
>>>>>
>>>>>
>>>>>
>>>>> On Wed, Oct 22, 2025 at 4:48 PM Paola Di Maio <paola.dimaio@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Gday AI KR CG
>>>>>>
>>>>>> Today DCMI 2025 Conference takes place in Barcelona, our paper was
>>>>>> accepted for presentation *in person only
>>>>>>
>>>>>> *pre recorded talk here
>>>>>>
>>>>>> https://drive.google.com/file/d/1ZXGxsFXvnTXm_knYXbax0I2HdqfWuNWK/view?usp=sharing
>>>>>>
>>>>> KRL vocab
>>>>>
>>>>>
>>>>> Some related work done in the last few years in this space is
>>>>> summarized in a recent narrative
>>>>>
>>>>> https://drive.google.com/file/d/1uZAw90qx1tPDbnVfGBSRCK260q-i8tzI/view?usp=sharing
>>>>>
>>>>> Here the slides where you may be able to open the links from the
>>>>> recording above
>>>>>
>>>>> https://drive.google.com/file/d/1uZAw90qx1tPDbnVfGBSRCK260q-i8tzI/view?usp=sharing
>>>>>
>>>>> *@TPAC 2025?  *https://www.w3.org/community/aikr
>>>>>> /wiki/AI_KR_CG_@TPAC_2025
>>>>>>
>>>>>
>>>>>
>>>>>> A mailing list, you can browse the archive here, where we try to keep
>>>>>> track of current topics in AI KR
>>>>>> https://lists.w3.org/Archives/Public/public-aikr/
>>>>>>
>>>>>> Some working notes on the wiki * may be outdated!
>>>>>> https://www.w3.org/community/aikr/wiki/Main_Page
>>>>>>
>>>>>> A first report published some time ago,
>>>>>> https://www.w3.org/community/aikr
>>>>>> /wiki/File:AI_KR_FIRST_REPORT_PUBLISHED_VERSION.pdf
>>>>>>
>>>>>
>>>>>
>>>>> Be good
>>>>>
>>>>>>