Cool idea, but the problem is that a huge factor in which sword wins is the combat environment, including the person wielding it (and the opponent). An inexperienced fighter with a rapier is going to get slaughtered by an experienced fighter with a broadsword. A long hand-and-a-half sword will be no good at all in a press of bodies or in a narrow corridor. A straight blade swung from horseback will just yank the sword out of your hand, or you off the horse, but a curved blade isn't strong enough to punch through mail. And so forth.

It's like you took all the vehicles in the world and did the same trick with them. What are you optimizing for? A vehicle that wins at the Indy 500 is not going to win at hauling steel rods to a muddy construction site.

On Sun, Apr 30, 2017 at 10:17 AM, Jeffrey Schwartz <xxxxxx@gmail.com> wrote:
Ran across this video - https://youtu.be/f60pAYKPXHs
A rating system for swords. Neat.

Then another thought collided with it.
Professor Lenat and EURISKO

Suppose you loaded thousands of swords into a database, then tagged
which ones were used in documented fights against others, and the rate
of win/loss.
Then ran some deep learning/genetic change algorithms against that
until you had a design that reliably won against everything else.

Then, since it was roughly the size of a cutlass, just called it that,
rather than some long UUID that the program came up with.
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