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

Rémi Coulom remi.coulom at free.fr
Thu Dec 7 08:51:22 PST 2017

>My concern about many of these points of comparison is that they presume how AZ scales. In the absence of data, I would guess that AZ gains much less from hardware than SF. I am basing this guess on >two known facts. First is that AZ did not lose a game, so the upper bound on its strength is perfection. Second, AZ is a knowledge intensive program, so it is counting on judgement to a larger degree.

Doesn't Figure 2 in the paper indicate convincingly that AZ scales better than Stockfish?


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