This reminds me an interesting question cryptographers deal with nowadays:

what is a secure cryptographic hash function.

In short (assuming you all know what a hash function is), a cryptographic
hash function is such that it is hard to find collisions (i.e., x and x' s.t.
h(x) = h(x')), second pre-image (given x finding x' s.t. h(x)=h(x')) and
pre-images (given y, find x s.t. h(x)=y).

The reason we have problems is that collisions must exist, and if a and b is
a collision than print(a,b) is a polynomial time algorithm which outputs the
collision.

Of course, this is dubious, because for any given hash function we might
know the specific algorithm. For more information about that, lock at
http://eprint.iacr.org/2006/281

In any case, there are infinite (Aleph zero) number of polynomial
algorithms, but there is (Aleph one) languages.
Actually, the only reason this is not a proof that P \neq NP is because the
size of NP is Aleph zero.
So indeed there are sufficiently many algorithms, but the question is
whether the number of languages the algorithms identify is infinite (please
note that two algorithms may identify the same language).

As for O(1) for all algorithms - there are many such languages.

For example, determining whether an input string is of the form a^n||b^n
requires reading the string (so the running time of any algorithm that
solves it is at least O(n)). There are even problems were you can prove that
you need extra memory of logarithmic size (see the connectivity problem).

And finally, the question whether P=NP does not necessarily require the
theory complexity to be complete. And given the definitions its quite
consistent (as long as polynomials are consistent).

Orr.
On 4/24/07, Uri Even-Chen <[EMAIL PROTECTED]> wrote:

On 4/24/07, Shachar Shemesh <[EMAIL PROTECTED]> wrote:
> Uri Even-Chen wrote:
> > Hi people,
> >
> > Recently I checked some problems in mathematics, computer science and
> > physics.  For a long time I had the intuition that the P vs NP Problem
> > is an undecidable problem.  I think the only conclusion we have is
> > that there is no solution, I don't think P and NP are mathematically
> > well defined.
> How so? For any given algorithm, the questions "is the algorithm
> polinomially bounded" and "is the algorithm non-deterministicly
> polinomially bounded" can be, fairly easilly, answered. That satisfy the
> group theory requirement for a "well behaved definition" for both P and
NP.
>
> Where is that flaw in the definition?

No theory can be both complete and consistent.  Every question we ask
affects the answer.  For example, the question "is the number 10
prime?" depends on whether 10 is a binary number or a decimal number
(or any base-n number).  I came to a conclusion that ANY well-defined
function can be computed in polynomial time (in theory).  There are
infinitely many algorithms.  It is not possible to prove that any
specific problem is not polynomial (unless it's not computable and
therefore not well defined).  Any such proof will contain some
uncertainty (or at least, cannot be proved not to contain uncertainty)
and therefore, it can be contradicted.

> > You can see my proof here:
> > http://www.speedy.net/uri/blog/?p=19
> Your terminology seems off. You appear to be using "O(n)" in a way that
> is inconsistent with the way it is defined in computer science, yet you
> provide no definition of your own for what it means. This is, of course,
> unless I totally mis-read your proof.

I'm referring to the general case, whether any specific problem is not
in O(1).  No specific problem can be proved not to be in O(1) for all
algorithms.

I also wrote more articles, for example a proof that the speed of
light is not constant (or more generally speaking, that deterministic
constants don't exist).  It means that there is no theoretical limit
to the speed any particle can travel in spacetime.  But I don't know
whether or not it applies to humans.  The term "human" itself is
intuitive and I don't think it can be defined physically in any
deterministic way which is not inconsistent.

http://www.speedy.net/uri/blog/?cat=3

Uri.

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Orr Dunkelman,
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