This is somewhat moot - if any moves had been significantly and obviously weak to any observers, the results wouldn't have been 4-1.
I.e. One bad move out of 5 games would give roughly the same strength information as one loss out of 5 games; consider that the kibitzing was being done in real time. s. On Mar 22, 2016 11:08 AM, "Jim O'Flaherty" <jim.oflaherty...@gmail.com> wrote: > I think you are reinforcing Simon's original point; i.e. using a more fine > grained approach to statically approximate AlphaGo's ELO where fine grained > is degree of vetting per move and/or a series of moves. That is a > substantially larger sample size and each sample will have a pretty high > degree of quality (given the vetting is being done by top level > professionals). > On Mar 22, 2016 1:04 PM, "Jeffrey Greenberg" <je...@inventivity.com> > wrote: > >> Given the minimal sample size, bothering over this question won't amount >> to much. I think the proper response is that no one thought we'd see this >> level of play at this point in our AI efforts and point to the fact that we >> witnessed hundreds of moves vetted by 9dan players, especially Michael >> Redmond's, where each move was vetted. In other words "was the level of >> play very high?" versus the question "have we beat all humans". The answer >> is more or less, yes. >> >> On Tuesday, March 22, 2016, Lucas, Simon M <s...@essex.ac.uk> wrote: >> >>> Hi all, >>> >>> I was discussing the results with a colleague outside >>> of the Game AI area the other day when he raised >>> the question (which applies to nearly all sporting events, >>> given the small sample size involved) >>> of statistical significance - suggesting that on another week >>> the result might have been 4-1 to Lee Sedol. >>> >>> I pointed out that in games of skill there's much more to judge than >>> just the final >>> outcome of each game, but wondered if anyone had any better (or worse :) >>> arguments - or had even engaged in the same type of >>> conversation. >>> >>> With AlphaGo winning 4 games to 1, from a simplistic >>> stats point of view (with the prior assumption of a fair >>> coin toss) you'd not be able to claim much statistical >>> significance, yet most (me included) believe that >>> AlphaGo is a genuinely better Go player than Lee Sedol. >>> >>> From a stats viewpoint you can use this approach: >>> http://www.inference.phy.cam.ac.uk/itprnn/book.pdf >>> (see section 3.2 on page 51) >>> >>> but given even priors it won't tell you much. >>> >>> Anyone know any good references for refuting this >>> type of argument - the fact is of course that a game of Go >>> is nothing like a coin toss. Games of skill tend to base their >>> outcomes on the result of many (in the case of Go many hundreds of) >>> individual actions. >>> >>> Best wishes, >>> >>> Simon >>> >>> >>> _______________________________________________ >>> Computer-go mailing list >>> Computer-go@computer-go.org >>> http://computer-go.org/mailman/listinfo/computer-go >> >> >> _______________________________________________ >> Computer-go mailing list >> Computer-go@computer-go.org >> http://computer-go.org/mailman/listinfo/computer-go >> > > _______________________________________________ > Computer-go mailing list > Computer-go@computer-go.org > http://computer-go.org/mailman/listinfo/computer-go >
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