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Comment by kirrent | Hacker News Reader

Even more interesting to me is the question of if Go players will be able to apply the novel strategies of AlphaGo which break with decades of conventional wisdom or if there's something in their execution that requires such perfect play (but leads to a more certain outcome) that they're only feasibly played by AlphaGo.

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That's the sort of thing I have wondered about. Chess continues to evolve since the famous Kasparov vs. Deep Blue matches, and from a quick look around human players do continue to draw matches against the strongest computers (even though they are regularly beaten, as well).

I'm not sure about human players, but it might be possible to build an adversarial neural network that beats AlphaGo (and only AlphaGo).

I thought AlphaGo is trained in an adversarial manner already (it plays against itself).

The version that played against Fan Hui was reportedly trained that way, but if I recall correctly the more recent one that played Lee Sedol did't rely on self-play as much.

Also the objective was different - they tried to train a network that would play well against any opponent. It should be easier to train a network that exploits some very narrow weakness in specific AlphaGo version.

For example, my phone consistently beats me at chess. But I found a sequence of moves in one opening where is always makes the same mistake, and I after that I can win easily.

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