On 23.10.2017 19:15, Xavier Combelle wrote:
[personal attack deleted]
Did you already encounter a real game with "disturbing life kos or
anti-sekis" and especially "ladders (...) beyond 250 moves" ? If not how
do you believe that Alphago would learn how to manage such situations.

Dave Dyer wrote:
I wonder how alphago-0 treats the menagerie of special positions, such as
bent 4 in the corner, thousand year ko, rotating ko, etc.

uurtamo wrote:
> It will be interesting to realize that those specialized positions
> (thousand-year-ko, bent 4) are actually a microscopic issue in
> game-winning.

The exceptional cases may be rarities in practical play but not all are that rare. E.g., I have had two games in roughly 40,000 ending with a double ko seki. Already one "rarity" occurring occasionally means that all rarities occur more often in practice. Therefore they do have practical relevance. Quite like a white truck is relevant and not to be confused with the sky, or an AI car can kill (which has happened because of such a "rarity"). In go, the consequences or misjudging "rarities" are just up a lost game, but this is the very purpose - avoiding lost games by avoiding errors. Rarities are good test samples for checking whether an AI program avoids errors in non-standard situations.

The same must be studied for standard situations, whose deeper details can also lead to errors. Not because a standard by itself would be difficult but because the deeper details increase complexity and this can lead to errors. Studying the standards and identifying errors in their deeper details can be difficult. E.g., we see AlphaGo (Zero) invading and living in a large moyo or not invading and wonder why. Part of the answer would be: invading and living is impossible. Studying this is complex because it involves deep reading for the standard case of a moyo and the question of invading it.

The "rarities" are infrequent but can be good test tools because distinguishing correct from wrong play can be easy if a rarity's behaviour is understood well. The standards are frequent but often not the best test tools because many standards interact with each other and they all depend on deep reading and exact positional judgement.

I cannot know if AlphaGo Zero has already learnt how to play in (some) rarities (those that can be solved earlier than the constant game end rule; e.g., we cannot test 4 octuple kos), will learn it or would not be able to learn it - but I want to know. In particular, because I want to know which errors AlphaGo Zero does make.

I want to know this for go and for the general AI project. Avoiding errors is essential for both. I do not fall into the illusion that AlphaGo Zero would be the perfect player but expect that it can make errors at any (unexpected) time. We need to understand what causes errors, how frequent they are and what most extreme consequences they can have. Rarities are one very good study tool for this purpose.

--
robert jasiek
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