[computer-go] Bot ratings and strength

[John Doe]

 I understand that some authors may not wish to reveal too many details of
their programs, but I am confused and a little frustrated by my inability to
make a bot that climbs even above 800 in rating on CGOS.  I am following a
fairly straightforward Monte Carlo style approach -- playing out random
simulations for each potential move from a position and choosing the one
that led to the most wins.  The random moves within the simulations avoid
filling single-point eyes (using the counting of corner-touching enemies
discussed on thi list) and playing into self-atari.  The top-level move
chosen to simulate next is based on the UCT-style algorithm, although I do
not (yet) keep any more of the tree in memory.  I have tried to make the
simulations as fast as possible; the number run is based on remaining time,
but is usually around 50,000 for a move.

My basic question is this: what makes some other similar programs so much
stronger?  I read the Sensai library descriptions for AnchorMan and
ControlBoy and see that they are very similar, yet do only 5,000
simulations, and yet are much much stronger programs overall.  Does this
difference come primarily from the benefits of keeping more of the tree in
memory?  From better heuristics for selecting top-level and/or simulation
moves?  I don't imagine anyone will have a completely definitive answer for
this, but I am just at a loss at this point.  Any guidance would be most
appreciated.

~ Jon
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