Subject: Finding the Optimal Super-Scan by Super-positioning Several Scans

From: Shlomi Fish <[email-masked]>
Date: Thu, 6 Dec 2001 04:45:49 +0200 (IST)

As many of you are aware I wrote a library to automatically solve Freecell
games. This library has many modes and options for operation, and for each
board some of them perform better than the others. Let's suppose I take a
group of such scans and measure the number of iterations each takes to
solve every board in a given board range.

Now I want to run a number of scans in an (let's say infinite) loop in
which I iterate over all the scans and run each of them for several
iterations until one of them reports the board as solveable or concludes
that it cannot be solved. Now I want this scheme to have the least
total number of iterations for the whole board.

Can anybody tell me of an algorithm that can construct the optimal scan
using data that specifies how many iterations each one of the components
require to solve the board? Note that I cannot modify the order in which I
perform the scans, because part of my incenitive is that this super-scan
will be suitable for other board ranges as well.

Regards,

	Shlomi Fish

----------------------------------------------------------------------
Shlomi Fish        [email-masked]
Home Page:         http://t2.technion.ac.il/~shlomif/
Home E-mail:       [email-masked]

If:
1. A is A
2. A is not not-A
does it imply that
1. B is B
2. B is not not-B