[Computer-go] ManyFaces vs Aya today (round 8 of the slow bottournament)

valkyria at phmp.se valkyria at phmp.se
Wed May 25 05:23:49 PDT 2011


I let Valkyria play from this position on an old single core P4. It  
plays out and wins the semeai even before it has to do so.

So by demonstrating this I have shown that with modest computational  
effort Valkyria thinks it is pretty simple. Or maybe more correctly:  
Valkyria can see moves that makes the game very simple.

So if Aya resigns a won position it means Aya needs to be improved not  
all go programs in general.

Also just because Valkyria plays reasonably well in this position does  
not mean that Valkyria is strong. It just happen to have enough  
knowledge to handle the tactics with a narrow search in this very  
position. I am sure there are a lot of positions Aya will outplay  
Valkyria.

Most MCTS programs used to be light in the sense close to buggy.

This is not more the case and the programs are getting stronger and  
stronger. But the process of adding knowledge is a trial and error  
process and different programmers have done different stuff. Also  
there is the tradeoff between speed and specialized knowledge. I  
always programmed Valkyria with no fear of slowing it down and I make  
any change that I think is necessary to play correctly even if the  
tactics are rare cases. Hence it tends to do well in positions where  
some program has serious problems. Overall though this does not make  
Valkyria the strongest program.

So my point is: for most non trivial tactical situations, some go  
programmers has a solution already. It is not hard to improve  
playouts. But it is very hard if not impossible to improve playouts  
for every possible special tactical position.

The question is : how do we tackle tactical positions in a general  
sense without slowing down playouts too much?

Semeai is a good example. Valkyria is good on simple cases close to  
the winning capture but there are an unending amount of complex semeai  
where this knowledge only have an effect deep down in the playouts.  
Some algorithm of online learning of good tactics seems to be necessary.

Best
Magnus

Quoting Stefan Kaitschick <Stefan.Kaitschick at Hamburg.de>:

> It's childishly simple for a human, large eye against small eye.
> Programmers need to find a way to make this a simple position for bots too.
> Solving it with great computational effort isn't good enough.
>
> Stefan
>
>> Aya resigned in winnning position...
>> http://files.gokgs.com/games/2011/5/24/ManyFaces1-AyaMC.sgf
>>
>> But in last position, to save B13 string,
>> kill B10.
>> to kill B10, play D6.
>> to play D6, kill B8.
>>
>> Semeai is really difficult.
>>
>> Hiroshi Yamashita
>>
>>
>> ----- Original Message ----- From: "David Fotland" <fotland at smart-games.com>
>> To: <computer-go at dvandva.org>; <nick at maproom.co.uk>
>> Sent: Wednesday, May 25, 2011 12:34 PM
>> Subject: [Computer-go] ManyFaces vs Aya today (round 8 of the slow   
>> bottournament)
>>
>>
>>> In this game, there was a big semeai on the left side.  The result  
>>>  was a won
>>> position for Aya, but both Aya and ManyFaces thought that ManyFaces had won
>>> (or perhaps that it was a semeai), so eventually Aya resigned before it was
>>> played out.
>>>
>>> A lucky win for ManyFaces, and a position for the report.
>>>
>>> David
>>>





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