On 8/20/10 12:21 PM, Alan wrote:
Thanks, I'll look into it. I know minimax ought to be easy to do but
it's a bit of a weak spot of mine - I can never seem to get it right,
and the poorish debug support in clojure, even with slime/swank,
doesn't make it easier.
I'm reasonably confident minimax/alpha-beta is right for me, since
it's not really an AI - I'm writing a "solution finder" which works
with perfect knowledge and has all the time it needs (though obviously
faster is better) to find the optimal solution. If anyone's
interested, it's specifically a double-dummy solver for the card game
bridge.
I stumbled across this implementation of alpha-beta in clojure on github:
http://github.com/rcrr/reversi/blob/master/strategies.clj#L251-282
It is a re-write of PAIP's CL version. (I didn't write it- just found it.)
-Ben
On Aug 16, 3:08 am, Mike Anderson<mike.r.anderson...@gmail.com>
wrote:
On Aug 13, 5:33 pm, Alan<a...@malloys.org> wrote:
Funny you should mention this - I was about to post a question about
my own game when I saw your article. My issue is, I assume someone has
written minimax and/or alpha-beta pruning in Clojure (or a java
library that's easy to interop with). My case is slightly different in
that the turn order is not fixes - sometimes player X goes twice in a
row - but it ought to be pretty simple to plug into a standard AI
library. Does anyone know where I can find such a thing?
I don't actually use alpha-beta: I opted to spend the effort to
develop
a decent evaluation function and then do some simple local
optimisation
on the gradient of said function.
My reasoning was that alpha-beta usually works best when the
branching
factor is low and the evaluation function pretty cheap to calculate,
sadly my situation was pretty much the reverse :-)
For your case it may be different. Two turns in a row works fine for
minimax or alpha-beta with a little tweaking (although it is likely
to
cut your search depth).
Be warned though - my experience is that it's rather hard to find an
AI library that will just "plug in" nicely to your code. Most of the
challenge in AI tends to be around special cases, embedding "expert"
knowledge and heuristics, plumbing in the right data representations
etc.
The search algorithm itself is usually the easy bit....
If you're after resources, there's a decent free online book on AI in
Java that might be useful, has lots of code examples that should be
pretty easy to convert to Clojure:
http://www.scribd.com/doc/6995538/Practical-AI-in-Java
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