Re: CGOS source on github
David Wu <[email protected]> Fri, 22 Jan 2021 09:39:24 -0500
| Newsgroups | gmane.games.devel.go |
|---|---|
| Message-ID | <CAGEydYt2yY85ttSYEkFzDO-GXA6jF4e_PO3m=-0gaKm3AAH09w@mail.gmail.com> |
--===============7207625461040262995== Content-Type: multipart/alternative; boundary="00000000000010ed5705b97e286d" --00000000000010ed5705b97e286d Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable @Claude - Oh, sorry, I misread your message, you were also asking about ladders, not just liberties. In that case, yes! If you outright tell the neural net as an input whether each ladder works or not (doing a short tactical search to determine this), or something equivalent to it, then the net will definitely make use of that information, There are some bad side effects even to doing this, but it helps the most common case. This is something the first version of AlphaGo did (before they tried to make it "zero") and something that many other bots do as well. But Leela Zero and ELF do not do this, because of attempting to remain "zero", i.e. free as much as possible from expert human knowledge or specialized feature crafting. On Fri, Jan 22, 2021 at 9:26 AM David Wu <[email protected]> wrote: > Hi Claude - no, generally feeding liberty counts to neural networks > doesn't help as much as one would hope with ladders and sekis and large > capturing races. > > The thing that is hard about ladders has nothing to do with liberties - a > trained net is perfectly capable of recognizing the atari, this is > extremely easy. The hard part is predicting if the ladder will work witho= ut > playing it out, because whether it works depends extremely sensitively on > the exact position of stones all the way on the other side of the board. = A > net that fails to predict this well might prematurely reject a working > ladder (which is very hard for the search to correct), or be highly > overoptimistic about a nonworking ladder (which takes the search thousand= s > of playouts to correct in every single branch of the tree that it happens > in). > > For large sekis and capturing races, liberties usually don't help as much > as you would think. This is because approach liberties, ko liberties, big > eye liberties, shared liberties versus unshared liberties, throwin > possibilities all affect the "effective" liberty count significantly. Als= o > very commonly you have bamboo joints, simple diagonal or hanging > connections and other shapes where the whole group is not physically > connected, also making the raw liberty count not so useful. The neural ne= t > still ultimately has to scan over the entire group anyways, computing the= se > things. > > On Fri, Jan 22, 2021 at 8:31 AM Claude Brisson via Computer-go < > [email protected]> wrote: > >> Hi. Maybe it's a newbie question, but since the ladders are part of the >> well defined topology of the goban (as well as the number of current >> liberties of each chain of stone), can't feeding those values to the >> networks (from the very start of the self teaching course) help with lar= ge >> shichos and sekis? >> >> Regards, >> >> Claude >> On 21-01-22 13 h 59, R=C3=A9mi Coulom wrote: >> >> Hi David, >> >> You are right that non-determinism and bot blind spots are a source of >> problems with Elo ratings. I add randomness to the openings, but it is >> still difficult to avoid repeating some patterns. I have just noticed th= at >> the two wins of CrazyStone-81-15po against LZ_286_e6e2_p400 were caused = by >> very similar ladders in the opening: >> http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2021/01/21/733333.sgf >> http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/2021/01/21/733301.sgf >> Such a huge blind spot in such a strong engine is likely to cause rating >> compression. >> >> R=C3=A9mi >> >> _______________________________________________ >> Computer-go mailing [email protected]://computer-go.or= g/mailman/listinfo/computer-go >> >> _______________________________________________ >> Computer-go mailing list >> [email protected] >> http://computer-go.org/mailman/listinfo/computer-go >> > --00000000000010ed5705b97e286d Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">@Claude - Oh, sorry, I misread your message, you were also= asking about ladders, not just liberties. In that case, yes! If you outrig= ht tell the neural net as an input whether each ladder works or not (doing = a short tactical search to determine this), or something equivalent to it, = then the net will definitely make use of that information, There are some b= ad side effects even to doing this, but it helps the most common case. This= is something the first version of AlphaGo did (before they tried to make i= t "zero") and something=C2=A0that many other bots do as well. But= Leela Zero and ELF do not do this, because=C2=A0of attempting to remain &q= uot;zero", i.e. free as much as possible from expert human knowledge o= r specialized feature crafting.<div><br></div></div><br><div class=3D"gmail= _quote"><div dir=3D"ltr" class=3D"gmail_attr">On Fri, Jan 22, 2021 at 9:26 = AM David Wu <<a href=3D"mailto:[email protected]">lightvector@gmail.= com</a>> wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"marg= in:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1e= x"><div dir=3D"ltr">Hi Claude - no, generally feeding liberty counts to neu= ral networks doesn't help as much as one would hope with ladders and se= kis and large capturing races.<div><br></div><div>The thing that is hard ab= out ladders has nothing to do with liberties - a trained net is perfectly c= apable=C2=A0of recognizing the atari, this is extremely easy. The hard part= is predicting if the ladder will work without playing it out, because whet= her it works depends extremely sensitively on the exact position of stones = all the way on the other side of the board. A net that fails to predict thi= s well might prematurely reject a working ladder (which is very hard for th= e search to correct), or be highly overoptimistic about a nonworking ladder= (which takes the search thousands of playouts to correct in every single b= ranch of the tree that it happens in).</div><div><br></div><div>For large s= ekis and capturing races, liberties usually don't help as much as you w= ould think. This is because approach liberties, ko liberties, big eye liber= ties, shared liberties versus unshared liberties, throwin possibilities all= affect the "effective" liberty count significantly. Also very co= mmonly you have bamboo joints, simple diagonal or hanging connections and o= ther shapes where the whole group is not physically connected, also making = the raw liberty count not so useful. The neural net still ultimately has to= scan over the entire group anyways, computing these things.</div></div><br= ><div class=3D"gmail_quote"><div dir=3D"ltr" class=3D"gmail_attr">On Fri, J= an 22, 2021 at 8:31 AM Claude Brisson via Computer-go <<a href=3D"mailto= :[email protected]" target=3D"_blank">[email protected]= </a>> wrote:<br></div><blockquote class=3D"gmail_quote" style=3D"margin:= 0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"> =20 =20 =20 <div> <p>Hi. Maybe it's a newbie question, but since the ladders are part of the well defined topology of the goban (as well as the number of current liberties of each chain of stone), can't feeding those values to the networks (from the very start of the self teaching course) help with large shichos and sekis?</p> <p>Regards,</p> <p>=C2=A0 Claude<br> </p> <div>On 21-01-22 13 h 59, R=C3=A9mi Coulom wrote:<br> </div> <blockquote type=3D"cite"> =20 <div dir=3D"ltr"> <div>Hi David,</div> <div><br> </div> <div>You are right that non-determinism and bot blind spots are a source of problems with Elo ratings. I add randomness to the openings, but it is still difficult to avoid repeating some patterns. I have just noticed that the two wins of CrazyStone-81-15po against LZ_286_e6e2_p400 were caused by very similar ladders in the opening:</div> <div><a href=3D"http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/20= 21/01/21/733333.sgf" target=3D"_blank">http://www.yss-aya.com/cgos/viewer.c= gi?19x19/SGF/2021/01/21/733333.sgf</a></div> <div><a href=3D"http://www.yss-aya.com/cgos/viewer.cgi?19x19/SGF/20= 21/01/21/733301.sgf" target=3D"_blank">http://www.yss-aya.com/cgos/viewer.c= gi?19x19/SGF/2021/01/21/733301.sgf</a></div> <div>Such a huge blind spot in such a strong engine is likely to cause rating compression.</div> <div><br> </div> <div>R=C3=A9mi<br> </div> </div> <br> <fieldset></fieldset> <pre>_______________________________________________ Computer-go mailing list <a href=3D"mailto:[email protected]" target=3D"_blank">Computer-g= [email protected]</a> <a href=3D"http://computer-go.org/mailman/listinfo/computer-go" target=3D"_= blank">http://computer-go.org/mailman/listinfo/computer-go</a> </pre> </blockquote> </div> _______________________________________________<br> Computer-go mailing list<br> <a href=3D"mailto:[email protected]" target=3D"_blank">Computer-g= [email protected]</a><br> <a href=3D"http://computer-go.org/mailman/listinfo/computer-go" rel=3D"nore= ferrer" target=3D"_blank">http://computer-go.org/mailman/listinfo/computer-= go</a><br> </blockquote></div> </blockquote></div> --00000000000010ed5705b97e286d-- --===============7207625461040262995== Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit Content-Disposition: inline _______________________________________________ Computer-go mailing list [email protected] http://computer-go.org/mailman/listinfo/computer-go --===============7207625461040262995==--