Re: limitations of classification systems, fiction, lack of ontological commitment

Daniel

I agree with your framing.

What I’ve been working on is precisely the operational layer (nl+math)
that connects mathematically grounded constructibility with KR-level
meaning and domain-specific constraints. In my model, domains of
discourse become executable contexts, and obligations defined in KR
are enacted through typed operational semantics and workflow rules.
This avoids universal hierarchies while still enabling computable,
auditable behavior across heterogeneous KR+math structures.

AgentIDL sits on a theory called CET I am developing. It treats
“existence” as a computable condition: representable as a type,
enactable through operational semantics, and verifiable through audit.
This bypasses the math-versus-KR debate entirely.

ref: https://figshare.com/articles/preprint/Computable_Existence_Theory_A_Formal_Axiom_System_for_Auditable_Artificial_Agency/30744605?backTo=%2Fcollections%2FComputable_Agency_Series_Volume_1%2F8175659&file=59974682

Daniel Ramos <capitain_jack@yahoo.com> 於 2025年11月30日週日 下午5:50寫道：
>
> Hi Milton, all,
>
> I just wanted to briefly echo one point Milton raised that I think is central for this CG:
>
> “We, I hope, strive to achieve a minimal set of structures and formalisms … for KR for AI.”
> “I have used the concept of domains of discourse … either in mathematical or natural language form.”
>
> From my side, working on Knowledge3D (K3D), I’ve found exactly the same: you can’t get to usable KR for AI without some mathematically grounded structure, but you also can’t stop at pure math—domains of discourse, provenance, and context have to be explicit.
>
> Concretely, in K3D we try to do this by:
>
> treating domains of discourse as explicit galaxies / Houses, not a single global space;
>
> representing form + meaning + rules together in K3D nodes (visual form, embeddings, RDF/OWL, and executable laws);
>
> keeping the mathematical substrate (RPN programs, embeddings) separate from, but tightly linked to, natural language and ontology layers.
>
> This has been very helpful in avoiding the “LLM ceiling” Milton describes: different domains can have different KR+math formalisms, but they still live in a shared, inspectable structure.
>
> I agree with Milton that we should avoid dogmatic “one true hierarchy” and instead focus on practical, computable KR structures for specific kinds of AI systems—making the mathematical and NL pieces work together, rather than treating one as “above” or “outside” the other.
>
> Best,
> Daniel
> Knowledge3D / AI‑RLWHF
> https://github.com/danielcamposramos/Knowledge3D

Received on Monday, 1 December 2025 02:03:41 UTC