> > > By conjecture, i suppose you mean that > no experiments yet has been ran as > to assess this hypothesis ? >
Yes. The other reasons were sufficient :-) I think Sylvain (and maybe just everyone else) has tried > at some point to use a UCT decision bot, as a way to > get the simulation done. Then using those high level > simulations in an other UCT decision tree (or AMAF, > or FirstMove wining stats) > From what i recall, the results were disappointing. > At least, it has been clearly established that "replacing the random player by a stronger player" does not imply "the Monte-Carlo program built on top of the random player becomes stronger" (even with fixed number of simulations) But, it is also clearly established that the building of the opening book by self-play clearly works, whereas it is roughly the same idea. I guess the reason is the difference of strength of the player - a MCTS (Monte-Carlo Tree Search - I don't write UCT here as it is not UCT in mogo) built on top of a perfect player should be a perfect player (this is formally obvious). So perhaps for huge computational power, this approach (building MCTS on top of MCTS) is consistent. > > For example, it is well known that Mogo-style decision > (or crazy stone) lead to very poor understanding of seki > (and/or semeai ?) Would'nt the use of high level game > as simulation get to better understanding of those > really nasty situations ? > I hope so, at least for 9x9 and with really huge computational power. (by the way I'm afraid we have to patch semeai manually) > > Is it that that it is known it would consume to much time and resources ? > I think it is really difficult to do that - you have to dump your results unless you have a machine for a huge time without any reboot, also if you want to have a huge computational effort you have to parallelize it - I think this is really hard. But perhaps trying mogo against mogo built on top of a mogo with e.g. 1s/move would be fine... this is easy to organize. Well, it requires some time, and time is always expensive :-) Best regards, Olivier
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