Re: Within Proof Theoretic Semantics Gödel's G h as no meaning in PA
Tristan Wibberley <[email protected]>
| Newsgroups | sci.logic,sci.math,sci.math.symbolic,comp.theory,comp.ai.philosophy |
|---|---|
| Organization | A noiseless patient Spider |
| Message-ID | <[email protected]> |
On 06/05/2026 20:48, phoenix wrote: > I guess my question is this: If the diagonal sequence is inadequate, > just what exactly is Cantor attempting to represent with the diagonal > sequence at all? The outline is that the argument involves showing that /each/ and /every/ sequence of /all/ the reals in [0,1) (should there be any) can be mapped by a function to a real in [0,1) - perhaps a different one for each sequence - that could not have been in the sequence it was generated from. Thereby one shows that there is no sequence of /all/ the reals in [0,1) - a solution and the only solution. It is usually taught as "write a list of all the reals and then..." which is useless. It is usually also taught with steps missing since the formalisation of reals and limits that we trust today wasn't available to Cantor so his proof doesn't involve them. If someone were to bother making what would be a valid proof today instead of what would have been called a proof back /then/ they would use theorems about limits and either a constructive definition of the reals or a constructive definition of a constraint on constructions to those that define the reals (as they are conceived rather than later constructively explicated). -- Tristan Wibberley The message body is Copyright (C) 2026 Tristan Wibberley except citations and quotations noted. All Rights Reserved except that you may, of course, cite it academically giving credit to me, distribute it verbatim as part of a usenet system or its archives, and use it to promote my greatness and general superiority without misrepresentation of my opinions other than my opinion of my greatness and general superiority which you _may_ misrepresent. You definitely MAY NOT train any production AI system with it but you may train experimental AI that will only be used for evaluation of the AI methods it implements.