Unfortunately there is no proof that you principles work better than those form eighties. Nor there is any agreement that your pronciples form any improvement over the old ones. Yes you are a far better player than me and shows that you are - way better at reading - have hugely better go understanding, principles if you like
What is missing that I doubt that you can verbalise your go understanding to degree that by applying those principles I could become substantially better player. again bulleting - My reading skills would not get any better hence making much of value any learning moot. Obviously issue on me not on your principles - your principles are more complex than you understand. Much of you know is automated to degree that it is subconsciousness information. Transferring that information if hard. Usually done by re-playing master games looking at problems i.e. training the darn neural net in the head If you can build Go bot about KGS 3/4dan strength I am more than willing to admit you are right and would even consider buying your books. Petri 2017-10-26 6:21 GMT+03:00 Robert Jasiek <jas...@snafu.de>: > On 25.10.2017 18:17, Xavier Combelle wrote: > >> exact go theory is full of hole. >> > > WRT describing the whole game, yes, this is the current state. Solving go > in a mathematical sense is a project for centuries. > > Actually, to my knowledge human can't apply only the exact go theory and >> play a decent game. >> > > Only for certain positions of a) late endgame, b) semeais, c) ko. > > If human can't do that, how it will teach a computer to do it magically ? >> > > IIRC, Martin Müller implemented CGT endgames a la Mathematical Go Endgames. > > The reason why (b) had became unpopular is because there is no go theory >> precise enough to implement it as an algorithm >> > > There is quite some theory of the 95% principle kind which might be > implemented as approximation. E.g. "Usually, defend your weak important > group." can be approximated by approximating "group", "important" (its loss > is too large in a quick positional judgement), "weak" (can be killed in two > successive moves), "defend" (after the move, cannot be killed in two > successive moves), "usually" (always, unless there are several such groups > and some must be chosen, say, randomly; the approximation being that the > alternative strategy of large scale exchange is discarded). > > Besides, one must prioritise principles to solve conflicting principles by > a higher order principle. > > IMO, such an expert system combined with tree reading and maybe MCTS to > emulate reading used when a principle depends on reading can, with an > effort of a few manyears of implementation, already achieve amateur mid > dan. Not high dan yet because high dans can choose advanced strategies, > such as global exchange, and there are no good enough principles for that > yet, which would also consider necessary side conditions related to > influence, aji etc. I need to work out such principles during the following > years. Currently, the state is that weaker principles have identified the > major topics (influence, aji etc.) to be considered in fights but they must > be refined to create 95%+ principles. > > *** > > In the 80s and 90s, expert systems failed to do better than ca. 5 kyu > because principles were only marginally better than 50%. Today, (my) > average principles discard the weaker, 50% principles and are ca. 75%. > Tomorrow, the 75% principles can be discarded for an average of 95% > principles. Expert systems get their chance again! Their major disadvantage > remains: great manpower is required for implementation. The advantage is > semantical understanding. > > -- > robert jasiek > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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