[Haskell-cafe] Code from "Why Functional Programming Matters"
wagner.andrew at gmail.com
Mon Sep 3 15:35:38 EDT 2007
I've been reading the classic "Why functional programming matters"
paper  lately, particularly looking at the alpha beta stuff. I've
ported all his code to haskell, but I have a question.
His algorithm takes a board position, creates a gametree out of it,
maps a static evaluation function over the gametree, then uses alpha
beta to find the real evaluation from a Tree Int. But of course, in an
actual application, what you actually want is the best MOVE from the
current position (or, even more ideally, the so-called "principal
variation", which is the best series of moves from the current
position). Is there a good way to collect this, without mapping some
sort of function over the tree that puts a list of moves on every node
Hughes seems to completely ignore this, and I wonder if it's because
it gets ugly to implement.
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