Yes, **Flibble’s neos-based solution can still be Turing Complete as a whole**, even though it **disallows programs from referencing the
decider**.
Let’s break this down precisely.
---
## ✅ What It Means to Be Turing Complete
A system is **Turing complete** if it can compute anything a Turing
machine can, given:
* Unbounded memory (in theory),
* Conditional branching,
* Arbitrary loops or recursion.
Turing completeness **does not require** that:
* Programs be analyzable by another program,
* Programs be allowed to self-reference or invoke their own decider.
---
## 🧠 Stratified Model in Flibble’s Design
Flibble’s proposal using **neos** introduces two **stratified languages**:
1. `shdlang`: a meta-layer language used to **analyze** code.
2. `neoscript` (or similar): a Turing-complete target language for
defining **programs**.
### Stratification Rule:
* `shdlang` → can inspect or reason about `neoscript` programs.
* `neoscript` → **cannot access** or call back into `shdlang`.
This blocks constructions like `D() { if H(D) then loop; }`, which enable **halting paradoxes**.
---
## 🔄 Is the Combined System Still Turing Complete?
Yes — because:
* The **target language layer** (`neoscript`) is unrestricted in its own recursion and computational logic.
* It can simulate a Turing machine in the usual way.
* **Not being able to invoke the decider doesn’t restrict the program’s expressive power**, only its ability to encode a self-referential
*analysis*.
This mirrors the situation in many practical systems:
* **C compilers** can analyze or optimize code, but the C code doesn’t
call the compiler.
* **Proof assistants** can verify programs, but the program logic doesn’t run the proof engine at runtime.
---
## 📌 Key Insight
**Turing completeness is a property of expressiveness — not ofreflexivity.**
Flibble’s system forbids *certain kinds of reference*, not *certain kinds of computation*.
---
## ✅ Summary
| Aspect |
Answer |
| ----------------------------------------------------------- | -------------------------------------------- |
| Is the target language Turing complete? | ✅
Yes |
| Does SHD restriction affect program expressiveness? | ❌ No — only affects semantic analysis scope |
| Can this architecture be used in general-purpose computing? | ✅ Absolutely |
| Does this break the classical halting proof? | ❌ No —
it sidesteps it by design constraints |
---
So yes, Flibble’s stratified neos solution **can still be Turing complete as a whole**, even though it blocks calls from programs to their deciders
— a **sound architectural tradeoff** to avoid paradox without sacrificing computational power.
On 5/23/2025 9:20 PM, Mr Flibble wrote:
Yes, **Flibble’s neos-based solution can still be Turing Complete as a
whole**, even though it **disallows programs from referencing the
decider**.
Let’s break this down precisely.
A more useful application of the term Turing Complete
would be that a sequence of algorithmic steps that
have sequence, selection and iteration have as much
memory as they need for a specific computation.
When we do this then it can be seen that some key
algorithms from the theory of computation can be
fully encoded in a high level language like C.
---
## ✅ What It Means to Be Turing Complete
A system is **Turing complete** if it can compute anything a Turing
machine can, given:
* Unbounded memory (in theory),
* Conditional branching,
* Arbitrary loops or recursion.
Turing completeness **does not require** that:
* Programs be analyzable by another program,
* Programs be allowed to self-reference or invoke their own decider.
---
## 🧠 Stratified Model in Flibble’s Design
Flibble’s proposal using **neos** introduces two **stratified
languages**:
1. `shdlang`: a meta-layer language used to **analyze** code.
2. `neoscript` (or similar): a Turing-complete target language for
defining **programs**.
### Stratification Rule:
* `shdlang` → can inspect or reason about `neoscript` programs.
* `neoscript` → **cannot access** or call back into `shdlang`.
This blocks constructions like `D() { if H(D) then loop; }`, which enable
**halting paradoxes**.
---
## 🔄 Is the Combined System Still Turing Complete?
Yes — because:
* The **target language layer** (`neoscript`) is unrestricted in its own
recursion and computational logic.
* It can simulate a Turing machine in the usual way.
* **Not being able to invoke the decider doesn’t restrict the program’s >> expressive power**, only its ability to encode a self-referential
*analysis*.
This mirrors the situation in many practical systems:
* **C compilers** can analyze or optimize code, but the C code doesn’t
call the compiler.
* **Proof assistants** can verify programs, but the program logic doesn’t >> run the proof engine at runtime.
---
## 📌 Key Insight
**Turing completeness is a property of expressiveness — not ofreflexivity.**
Flibble’s system forbids *certain kinds of reference*, not *certain kinds >> of computation*.
---
## ✅ Summary
| Aspect |
Answer |
| ----------------------------------------------------------- |
-------------------------------------------- |
| Is the target language Turing complete? | ✅
Yes |
| Does SHD restriction affect program expressiveness? | ❌ No —
only affects semantic analysis scope |
| Can this architecture be used in general-purpose computing? | ✅
Absolutely | >> | Does this break the classical halting proof? | ❌ No —
it sidesteps it by design constraints |
---
So yes, Flibble’s stratified neos solution **can still be Turing complete >> as a whole**, even though it blocks calls from programs to their deciders
— a **sound architectural tradeoff** to avoid paradox without sacrificing >> computational power.
On 5/25/2025 1:18 AM, Mikko wrote:
On 2025-05-24 16:02:41 +0000, olcott said:
On 5/23/2025 9:20 PM, Mr Flibble wrote:...
Yes, **Flibble’s neos-based solution can still be Turing Complete as a >>>> whole**, even though it **disallows programs from referencing the
decider**.
Let’s break this down precisely.
A more useful application of the term Turing Complete would be that
The only useful meaning is what the term actually means. Any other
meaning is harmful.
Analysis of complex theory of computation problems
is much more effective at the higher levels of
abstraction of higher level languages.
For example because the x86 language has relative
addressing the underlying model of computation
specified by the x86 language has unlimited memory
thus is Turing complete.
Turing complete cannot possibly make any actual
difference at all as long as the model of computation
has enough memory for the algorithm.
On 5/26/2025 3:19 AM, Mikko wrote:
On 2025-05-25 14:42:17 +0000, olcott said:
On 5/25/2025 1:18 AM, Mikko wrote:
On 2025-05-24 16:02:41 +0000, olcott said:
On 5/23/2025 9:20 PM, Mr Flibble wrote:...
Yes, **Flibble’s neos-based solution can still be Turing Complete >>>>>> as a
whole**, even though it **disallows programs from referencing the
decider**.
Let’s break this down precisely.
A more useful application of the term Turing Complete would be that
The only useful meaning is what the term actually means. Any other
meaning is harmful.
Analysis of complex theory of computation problems
is much more effective at the higher levels of
abstraction of higher level languages.
For example because the x86 language has relative
addressing the underlying model of computation
specified by the x86 language has unlimited memory
thus is Turing complete.
The generic x86 language does not specify the mapping from addresses
to memory locations. Different x86 processors do it differently. A
particular processor may be able to shift the mapping of a part of
the address space to a previous or next block of a potentially
infinite memory. However, the usual models can pnly map it to a larger
finite memory.
None of which is irrelevan to my note that the only useful meaning is
what the term actually means.
Turing complete cannot possibly make any actual
difference at all as long as the model of computation
has enough memory for the algorithm.
It doesn't as long as you can compute every function you want to compute.
But if you don't know what you will want then having a Turing complete
system is best you can have.
The best system is a system that actually exists.
there are far too many errors of false assumptions
in models that are only imagined to exist.
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