[Computer-go] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

David Wu lightvector at gmail.com
Wed Dec 6 07:42:05 PST 2017


This is not on a 19x19 board, and it was not tested against the current
state of the art (Mohex 1.0 was the state of the art at its time, but is at
least several years old now, I think), but they do get several hundred elo
points stronger than this old version of Mohex, have training curves that
suggest that they still haven' reached the limit of improvement, and are
doing it with orders of magnitude less computation than Google would have

So, I think it is likely that hex is not going to be too difficult for
AlphaZero or similar architecture.

On Wed, Dec 6, 2017 at 9:28 AM, "Ingo Althöfer" <3-Hirn-Verlag at gmx.de>

> It seems, we are living in extremely
> heavy times ...
> I want to go to bed now and meditate for threee days.
> > DeepMind makes strongest Chess and Shogi programs with AlphaGo Zero
> method.
> > Mastering Chess and Shogi by Self-Play with a General Reinforcement
> Learning Algorithm
> > https://arxiv.org/pdf/1712.01815.pdf
> >
> > AlphaZero(Chess) outperformed Stockfish after 4 hours,
> > AlphaZero(Shogi) outperformed elmo after 2 hours.
> It may sound strange, but at the moment my only hopes for
> games too difficult for AlphaZero might be
> * a connection game like Hex (on 19x19 board)
> * a game like Clobber (based on CGT)
> Mastering Clobber would mean that also the concept of
> combinatorial game theory would be "easily" learnable.
> Side question: Would the classic Nim game be
> a trivial nut for AlphaZero ?
> Ingo (is now starting to hope for an AlphaZero type program
> that can do "general" mathematical research).
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