On Sun, Mar 10, 2019 at 5:29 PM Lawrence Crowell <
goldenfieldquaterni...@gmail.com> wrote:

*> in the biological world certain problems that are NP are figured out.
> This runs from ants finding the minimal distance for their trails or even
> protistans negotiating some space. Ants are good at approximately solving
> the traveling salesman problem, the classic NP algorithm.*


It's easy to solve the traveling salesman problem if the number of cities
involved is small, but I see no evidence that nature can in general solve
NP problems in polynomial time. Of course there are many claims to the
contrary so Quantum Computer expert Scott Aaronson decided to but the
matter to a simple experimental test, this is what he reported:


*"taking two glass plates with pegs between them, and dipping the resulting
contraption into a tub of soapy water. The idea is that the soap bubbles
that form between the pegs should trace out the minimum Steiner tree — that
is, the minimum total length of line segments connecting the pegs,
where the segments can meet at points other than the pegs themselves. Now,
this is known to be an NP-hard optimization problem. So, it looks like
Nature is solving NP-hard problems in polynomial time!*

*Long story short, I went to the hardware store, bought some glass plates,
liquid soap, etc., and found that, while Nature does often find a minimum
Steiner tree with 4 or 5 pegs, it tends to get stuck at local optima with
larger numbers of pegs. Indeed, often the soap bubbles settle down to
a configuration which is not even a tree (i.e. contains “cycles of soap”),
and thus provably can’t be optimal.*

*The situation is similar for protein folding. Again, people have said that
Nature seems to be solving an NP-hard optimization problem in every cell of
your body, by letting the proteins fold into their minimum-energy
configurations. But there are two problems with this claim. The first
problem is that proteins, just like soap bubbles, sometimes get stuck in
suboptimal configurations — indeed, it’s believed that’s exactly what
happens with Mad Cow Disease. The second problem is that, to the
extent that proteins do usually fold into their optimal configurations,
there’s an obvious reason why they would: natural selection! If  there were
a protein that could only be folded by proving the Riemann Hypothesis, the
gene that coded for it would quickly get weeded out of the gene pool." *


> *> The ants crawl all over the place and the trails with the largest
> pheremone density tend to be those that are a solution or near solution to
> the traveling salesman problem.*


It's not difficult to good solutions to the traveling salesman problem but
it's very hard to find a the perfect solution or even to check that a
proposed answer is indeed the best there is. I don't believe ants can in
general find the perfect solution, but even if they did being a NP problem
there is no efficient way to even check the answer, so how in the would
could you know it was the perfect solution?

John K Clark



>

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