David said "estimate final score" which implies that all relevant things are factored in, merely the unit of estimation is territory. Just like in chess there are several things factored in - other than material - and all are estimated as pawns.
I guess expert systems really are a dead end in Go. Too many contradicting heurestics 2015-09-09 10:31 GMT+03:00 Robert Jasiek <jas...@snafu.de>: > On 09.09.2015 07:42, David Fotland wrote: > >> I classify groups instead. Each classification is treated differently >> when estimating territory, when generating candidate moves, etc. >> > > This is reasonable. > > The territory counts depend on the strength of the nearby groups. >> > > Whether this is good depends on how you link strengths to counts. > > *** > > Was your influence function like radiated light? Such would have too > little meaning. > > Monte Carlo has a big advantage in that it estimates the probability of >> winning the game, rather than my old approach of trying to estimate the >> final score. >> > > Whether it is an advantage depends on one's objectives. > > For an expert system, estimating the score is just one aspect for further > application and does not finish the job. (To start with, a positional > judgement consists of more than the 'territory count' and group strengths > of the current position.) > > > -- > robert jasiek > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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