Re:AlphaGo Zero: Learning from scratch
by chrchang523 on Wednesday October 18, 2017 @04:54PM
(#15502961)
The absolute value of any Go board position is well-defined, and MCTS provides good computationally tractable approximations that get better as the rest of the system improves but already start better than random.
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Re:AlphaGo Zero: Learning from scratch
by time-of-flight on Thursday October 19, 2017 @10:12AM
(#15508021)
Check the Nature paper (and I think this is one of the biggest take-aways from AlphaGo Zero):
"Finally, it uses a simpler tree search that relies upon this single neural network to evaluate positions and sample moves, without performing any Monte Carlo rollouts."
In this new version, MCTS is not even used to evaluate a position! Speaking as a Go player, the ability for the neural network to accurately evaluate a position without "reading" ahead is phenomenal (again, read the Nature paper last page for details).
the absolute value of a go board position is well defined? where?
As a human go player I can say that evaluating board position is close to impossible.
You may have a seemingly good position and in two turns it seems that you have lost the game already.