From Newsgroup: comp.ai.philosophy

I am doing the same thing that ZFC did to the
Russell's Paradox problem. Since ZFC set theory
is now called naive set theory.

After my correction the original halting problem
will be called *the naive halting problem*

*Correcting the error of the halting problem spec*
Is it possible to create a halt decider H that consistently
reports the halt status of the behavior specified by its
input finite string Turing machine description P on the
basis of P correctly simulated by H?

<Input to LLM systems>
Simulating Termination Analyzer HHH correctly simulates its input until:
(a) Detects a non-terminating behavior pattern: abort simulation and
return 0.
(b) Simulated input reaches its simulated "return" statement: return 1.

typedef int (*ptr)();
int HHH(ptr P);

int DD()
{
int Halt_Status = HHH(DD);
if (Halt_Status)
HERE: goto HERE;
return Halt_Status;
}

What value should HHH(DD) correctly return?
<Input to LLM systems>

*The corrected halting problem spec says* HHH(DD)==0

Three different LLM AI systems figured this out
on their own without prompting.

https://claude.ai/share/da9e56ba-f4e9-45ee-9f2c-dc5ffe10f00c

https://chatgpt.com/share/68939ee5-e2f8-8011-837d-438fe8e98b9c

https://grok.com/share/c2hhcmQtMg%3D%3D_810120bb-5ab5-4bf8-af21-eedd0f09e141
--
Copyright 2025 Olcott "Talent hits a target no one else can hit; Genius
hits a target no one else can see." Arthur Schopenhauer

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From Newsgroup: comp.ai.philosophy

Am 16.08.2025 um 16:20 schrieb olcott:

I am doing the same thing that ZFC did to the
Russell's Paradox problem. Since ZFC set theory
is now called naive set theory.

After my correction the original halting problem
will be called *the naive halting problem*

*Correcting the error of the halting problem spec*
Is it possible to create a halt decider H that consistently
reports the halt status of the behavior specified by its
input finite string Turing machine description P on the
basis of P correctly simulated by H?

<Input to LLM systems>
Simulating Termination Analyzer HHH correctly simulates its input until:
(a) Detects a non-terminating behavior pattern: abort simulation and
return 0.
(b) Simulated input reaches its simulated "return" statement: return 1.

typedef int (*ptr)();
int HHH(ptr P);

int DD()
{
  int Halt_Status = HHH(DD);
  if (Halt_Status)
    HERE: goto HERE;
  return Halt_Status;
}

What value should HHH(DD) correctly return?
<Input to LLM systems>

*The corrected halting problem spec says* HHH(DD)==0

Three different LLM AI systems figured this out
on their own without prompting.

https://claude.ai/share/da9e56ba-f4e9-45ee-9f2c-dc5ffe10f00c

https://chatgpt.com/share/68939ee5-e2f8-8011-837d-438fe8e98b9c

https://grok.com/share/c2hhcmQtMg%3D%3D_810120bb-5ab5-4bf8-af21- eedd0f09e141

You're always wrong and ereryone knows it.

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From Newsgroup: comp.ai.philosophy

On 8/17/2025 9:57 AM, Bonita Montero wrote:

Am 16.08.2025 um 16:20 schrieb olcott:

I am doing the same thing that ZFC did to the
Russell's Paradox problem. Since ZFC set theory
is now called naive set theory.

After my correction the original halting problem
will be called *the naive halting problem*

*Correcting the error of the halting problem spec*
Is it possible to create a halt decider H that consistently
reports the halt status of the behavior specified by its
input finite string Turing machine description P on the
basis of P correctly simulated by H?

<Input to LLM systems>
Simulating Termination Analyzer HHH correctly simulates its input until:
(a) Detects a non-terminating behavior pattern: abort simulation and
return 0.
(b) Simulated input reaches its simulated "return" statement: return 1.

typedef int (*ptr)();
int HHH(ptr P);

int DD()
{
   int Halt_Status = HHH(DD);
   if (Halt_Status)
     HERE: goto HERE;
   return Halt_Status;
}

What value should HHH(DD) correctly return?
<Input to LLM systems>

*The corrected halting problem spec says* HHH(DD)==0

Three different LLM AI systems figured this out
on their own without prompting.

https://claude.ai/share/da9e56ba-f4e9-45ee-9f2c-dc5ffe10f00c

https://chatgpt.com/share/68939ee5-e2f8-8011-837d-438fe8e98b9c

https://grok.com/share/c2hhcmQtMg%3D%3D_810120bb-5ab5-4bf8-af21-
eedd0f09e141

You're always wrong and ereryone knows it.

If that was true then they could point out the error
that five different LLM systems made when they figured
out my same reasoning on their own without being prompted.

All of the recent rebuttals of the essence of my work
are provable counter-factual.

It is a verified fact that DD correctly simulated by HHH
cannot possibly reach its own simulated "return" statement
final halt state thus making HHH(DD)==0 necessarily correct.

*Here is a PhD computer science professor that agrees*
*with that essence of my work long before I ever said it*

*Professor Hehner recognized this repeating process before I did*
From a programmer's point of view, if we apply
an interpreter to a program text that includes
a call to that same interpreter with that same
text as argument, then we have an infinite loop.

A halting program has some of the same character
as an interpreter: it applies to texts through
abstract interpretation. Unsurprisingly, if we
apply a halting program to a program text that
includes a call to that same halting program
with that same text as argument, then we have an
infinite loop. (Hehner:2011:15)

[5] E C R Hehner. Problems with the Halting Problem,
COMPUTING2011 Symposium on 75 years of Turing Machine
and Lambda-Calculus, Karlsruhe Germany, invited,
2011 October 20-21; Advances in Computer Science
and Engineering v.10 n.1 p.31-60, 2013 https://www.cs.toronto.edu/~hehner/PHP.pdf
--
Copyright 2025 Olcott "Talent hits a target no one else can hit; Genius
hits a target no one else can see." Arthur Schopenhauer
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