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I tried the following, but they all made things worse:
- moving away from the singly-linked (tail tracking) list for actions
by:
+ using an array zipper for a deque
+ using an array to poorly hold a floating deque
- caching the results of generating move lists in the transposition
table and then
+ copying the resulting list/zip/deque instead of generating it
+ applying the move-to-front without copying, but this made the
search order worse. Presumably in this case shallower nodes were
messing up the search tree with garbage moves?
I think some of this is not supposed to happen, but i have just the
right combination of poor evaluation function and naively ordered and
cheap move generation that i'm in a local minimum here.
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Eventually there'll be a more complicated data generation step than
the one we're presently using, so having it in-lined in the loop is
wasteful. Ideally also this would be update per ply and we could avoid
recalculating it entirely for every query -- though it's probably
``fast enough'' for now. Also, caching is WIP.
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It turns out that while i was training on a 0/1 classification
problem, i was using 2*eval - 1. Training using this function instead,
and on bot-dominated game choices (chosen_player in extract.sh) seems
to have given a better evaluation function. At the least, Morten's
swindle doesn't work anymore.
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