Re: [Computer-go] AlphaGo & DCNN: Handling long-range dependency

[Huazuo Gao]

Points at the center of the board indeed depends on the full board, but
points near the edge does not.

On Fri, Mar 11, 2016 at 3:03 PM Vincent Zhuang  wrote:

> A stack of 11 3x3 convolutional layers and a single 5x5 layer with no
> pooling actually corresponds to effectively a 27x27 kernel, which is
> obviously large enough to cover the entire board. (Your value of 13 is only
> the distance from the center of the filter to the edge).
>
>
> On Thu, Mar 10, 2016 at 10:48 PM, Huazuo Gao  wrote:
>
>> According to the paper *Mastering the Game of Go with Deep Neural
>> Networks and **Tree Search*, the main part of both the policy and value
>> network is a 5*5 conv layer followed by eleven 3*3 conv layer. Therefore,
>> after the last conv layer, the maximum "information propagation length" is
>> (5-1)/2 + 11*(3-1)/2 = 13, which is insufficient for covering the full
>> board.
>>
>> It might not have been a big problem though, as tree search and MC
>> rollouts should mitigate most deficiencies to a large extent. However,
>> during the opening, realising the correlation between distant stones would
>> be quite important, provided that tree search would not help much while MC
>> rollouts might not provide a unbiased view.
>>
>> It seems to me that DCNN are not perfect for Go. Anyway, apparently
>> that's enough for beating top human level.
>>
>> ___
>> 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

Re: [Computer-go] AlphaGo & DCNN: Handling long-range dependency

[Vincent Zhuang]

A stack of 11 3x3 convolutional layers and a single 5x5 layer with no
pooling actually corresponds to effectively a 27x27 kernel, which is
obviously large enough to cover the entire board. (Your value of 13 is only
the distance from the center of the filter to the edge).


On Thu, Mar 10, 2016 at 10:48 PM, Huazuo Gao  wrote:

> According to the paper *Mastering the Game of Go with Deep Neural
> Networks and **Tree Search*, the main part of both the policy and value
> network is a 5*5 conv layer followed by eleven 3*3 conv layer. Therefore,
> after the last conv layer, the maximum "information propagation length" is
> (5-1)/2 + 11*(3-1)/2 = 13, which is insufficient for covering the full
> board.
>
> It might not have been a big problem though, as tree search and MC
> rollouts should mitigate most deficiencies to a large extent. However,
> during the opening, realising the correlation between distant stones would
> be quite important, provided that tree search would not help much while MC
> rollouts might not provide a unbiased view.
>
> It seems to me that DCNN are not perfect for Go. Anyway, apparently that's
> enough for beating top human level.
>
> ___
> 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] AlphaGo & DCNN: Handling long-range dependency

[Huazuo Gao]

According to the paper *Mastering the Game of Go with Deep Neural Networks
and **Tree Search*, the main part of both the policy and value network is a
5*5 conv layer followed by eleven 3*3 conv layer. Therefore, after the last
conv layer, the maximum "information propagation length" is (5-1)/2 +
11*(3-1)/2 = 13, which is insufficient for covering the full board.

It might not have been a big problem though, as tree search and MC rollouts
should mitigate most deficiencies to a large extent. However, during the
opening, realising the correlation between distant stones would be quite
important, provided that tree search would not help much while MC rollouts
might not provide a unbiased view.

It seems to me that DCNN are not perfect for Go. Anyway, apparently that's
enough for beating top human level.
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Finding Alphago's Weaknesses

[David Fotland]

He was already in Byo-yomi, so perhaps he didn’t have an accurate count. This 
might explain why he looked upset at move 175.  He might have realized his 
mistake.

David

> -Original Message-
> From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf
> Of Darren Cook
> Sent: Thursday, March 10, 2016 8:26 AM
> To: computer-go@computer-go.org
> Subject: Re: [Computer-go] Finding Alphago's Weaknesses
> 
> > In fact in game 2, white 172 was described [1] as the losing move,
> > because it would have started a ko. ...
> 
> "would have started a ko" --> "should have instead started a ko"
> 
> ___
> 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] AlphaGo's time management

[Seo Sanghyeon]

Undoubtedly many things happened since October, but Wired article
includes an interesting quote on AlphaGo's time management.

http://www.wired.com/2016/03/googles-ai-wins-first-game-historic-match-go-champion/

"At the lunch prior to the match, Hassabis also said that since
October, he and his team had also used machine learning techniques to
improve AlphaGo's ability to manage time."

I wonder how much did it help. I hope it is published in the future.

-- 
Seo Sanghyeon
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Finding Alphago's Weaknesses

[uurtamo .]

Not to put too fine a point on it, but there's not very many two or
three-move combos on an empty board. As staggering as it is, I'm inclined
to believe without further evidence that there's no book or just a very
light book.

s.
On Mar 10, 2016 7:50 PM, "Seo Sanghyeon"  wrote:

> 2016-03-11 11:42 GMT+09:00 terry mcintyre :
> > Hypothetically, they could have grafted one on. I read a report that the
> > first move in game 2 vs. Lee Sedol took only seconds. On the other hand,
> > it's first move in game 1 took a longer while. We can only speculate.
>
> This is easy to explain. AlphaGo was white (second to play) in game 1,
> and black (first to play) in game 2. You can precalculate a move if you are
> first to play. Harder to do that if you are second.
>
> --
> Seo Sanghyeon
> ___
> 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

Re: [Computer-go] Finding Alphago's Weaknesses

[Seo Sanghyeon]

2016-03-11 11:42 GMT+09:00 terry mcintyre :
> Hypothetically, they could have grafted one on. I read a report that the
> first move in game 2 vs. Lee Sedol took only seconds. On the other hand,
> it's first move in game 1 took a longer while. We can only speculate.

This is easy to explain. AlphaGo was white (second to play) in game 1,
and black (first to play) in game 2. You can precalculate a move if you are
first to play. Harder to do that if you are second.

-- 
Seo Sanghyeon
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Finding Alphago's Weaknesses

[terry mcintyre]

 blockquote, div.yahoo_quoted { margin-left: 0 !important; border-left:1px 
#715FFA solid !important;  padding-left:1ex !important; background-color:white 
!important; }  According to the paper, AlphaGo did not use an opening book at 
all, in the version which played Fan Hui.
Hypothetically, they could have grafted one on. I read a report that the first 
move in game 2 vs. Lee Sedol took only seconds. On the other hand, it's first 
move in game 1 took a longer while. We can only speculate. 


Sent from Yahoo Mail for iPad


On Thursday, March 10, 2016, 12:31 PM, uurtamo .  wrote:


Quick question - how, mechanically, is the opening being handled by alpha go 
and other recent very strong programs? Giant hand-entered or game-learned 
joseki books?

Thanks,

steve
On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:

My 2 cent:

Recent strong computer programs never loose by a few points.  They are either
crashed before the end game starts (because when being clearly behind they play 
more
desperate and weaker moves because they mainly get negative feadback from
their search with mostly loosing branches and risky play gives them the only
winning sequences in their search) or they win by resignation or win
by a few points.

In other words, if a human player playing AlphaGo does not have a large
advantage already in the middle game, then AlphaGo will win whether it looks
like it or not (even to a 9p player like Michael Redmond was surprised
last night about the sudden gain of a number of points by AlphaGo in the
center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video 
https://gogameguru.com/alphago-2/)

In the middle and end game the reduced number of possible moves and the
precise and fast counting ability of computer programs are superior.  In the
game commentary of the 1st game it was mentioned that Lee Sedol considers the
opening not to be his strongest part of the game.  But with AlphaGo playing
top pro level even in the opening, a large advantage after the middle game
might simply be impossible to reach for a human.

About finding weakness:
In the absense of games of AlphaGo to study it might be interesting to get a 
general idea by checking out the games where 7d Zen lost on KGS
recently.

Thomas

On Thu, 10 Mar 2016, wing wrote:


One question is whether Lee Sedol knows about these weaknesses.
Another question is whether he will exploit those weaknesses.
Lee has a very simple style of play that seems less ko-oriented
than other players, and this may play into the hands of Alpha.

Michael Wing


 I was surprised the Lee Sedol didn't take the game a bit further to
 probe AlphaGo and see how it responded to [...complex kos, complex ko
 fights, complex sekis, complex semeais, ..., multiple connection
 problems, complex life and death problems] as ammunition for his next
 game. I think he was so astonished at being put into a losing
 position, he wasn't mentally prepared to put himself in a student's
 role again, especially to an AI...which had clearly played much weaker
 games just 6 months ago. I'm hopeful Lee Sedol's team has been some
 meta-strategy sessions where, if he finds himself in a losing position
 in game two, he turns it into exploring a set of experiments to tease
 out some of the weaknesses to be better exploited in the remaining
 games.

 On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  wrote:

>  On 10.03.2016 00:45, Hideki Kato wrote:
> > >  such as solving complex semeai's and double-ko's, aren't solved yet.
> >  To find out Alphago's weaknesses, there can be, in particular,
> >  - this match
>  - careful analysis of its games
>  - Alphago playing on artificial problem positions incl. complex kos, >  
>complex ko fights, complex sekis, complex semeais, complex endgames, >  
>multiple connection problems, complex life and death problems (such as >  Igo 
>Hatsu Yoron 120) etc., and then theoretical analysis of such play
>  - semantic verification of the program code and interface
>  - theoretical study of the used theory and the generated dynamic data >  
>(structures)
> >  --
>  robert jasiek
>  ___
>  Computer-go mailing list
>  Computer-go@computer-go.org
>  http://computer-go.org/mailman/listinfo/computer-go [1]



 Links:
 --
 [1] 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


___
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

Re: [Computer-go] Finding Alphago's Weaknesses

[Brian Sheppard]

Amen to Don Dailey. He would be so proud.

 

From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf Of Jim 
O'Flaherty
Sent: Thursday, March 10, 2016 6:49 PM
To: computer-go@computer-go.org
Subject: Re: [Computer-go] Finding Alphago's Weaknesses

 

I think we are going to see a case of human professionals having drifted into a 
local optima in at least three areas:

  1) Early training around openings is so ingrained in their acquiring their 
skill (optimal neural plasticity window), there has been very little new 
discovery around the first third of the game with almost all professionals 
relying fairly strongly on the already time tested josekis - AIs can use 
reading to explore closer and closer to the start of a game using less and less 
automatic patterns thereby confusing humans who have memorized those patterns

  2) The middle of the board is so high in reading complexity, there has been 
little investment to figure out how to leverage it until mid game as it has 
been more expedient to focus on the corners and edges - AIs are going to get 
faster, better and deeper at reading through and then intentionally generating 
complexity

  3) As a human's cognition tires, the probability of reading errors rises 
non-linearly which increases the probability of late mid-game and end game 
errors - I think AlphaGo has already progressed pretty far in the end game

 

I'd consider these the three primary general vulnerabilities of human Go 
playing against any future AI. Given AlphaGo's training mechanism is actually 
search space exploration engine, it will slowly but surely explore and converge 
on more optimal play in all three of these domains significantly faster and 
cheaper than directly investing in and expending human cognition efforts; i.e. 
professionals studying to do the knowledge expansion and verification. And I 
think they will continue to optimize AlphaGo's algorithms in both human and 
self-play.

 

The window where humans are going to be able to fish out a win against AlphaGo 
is rapidly closing...and it may have already closed.

 

 

Other thoughts...

 

I think we are going to see some fascinating "discoveries" of errors in 
existing very old josekis. At some point, I think we will even see one or two 
new ones discovered by AIs or by humans exploiting AIs. We are going to see 
some new center oriented fighting based on vastly more complex move sequences 
which will result in an substantial increase in resignations at the 
professional level against each other. 

 

Said a slightly different way...even if Lee Sedol figures how how to get a lead 
in a game during the opening, AlphaGo will just continue to elevate the board 
complexity with each move until it is just beyond its opponent's reading 
ability while staying well within it's own reading ability constraints. IOW, 
complexity is now an AIs advantage. AlphaGo doesn't have the human frailty of 
being nervous of a possible future mistake and then altering its priorities by 
pushing winning by a higher margin as a buffer against said future reading 
complexity mistake. IOW, AlphaGo is regulated by it's algorithm's prioritizing 
the probability of win higher than the amount of margin by which it could 
buffer for a win. What seems like a weakness is turning out to be one hell of a 
strength.

 

Add to the fact that this kind of behavior by AlphaGo is denying it's opponent 
critical information about the state of the game which is more readily 
available in human-vs-human games; i.e. AlphaGo's will continue to converge 
towards calmer and calmer play in the face of chaotic play. And the calmer it 
becomes, the less "weakness surface area" it will have for a human to exploit 
in attempting a win.

 

This is utterly fascinating to get to witness. I sure wish Don Daily was still 
here to get to enjoy this.

 

 

On Thu, Mar 10, 2016 at 2:52 PM, Thomas Wolf  > wrote:

With at most 2x361 or so different end scores but 10^{XXX} possible different
games, there are at least in the opening many moves with the same optimal
outcome. The difference between these moves is not the guaranteed score (they
are all optimal) but the difficulty to play optimal after that move. And the
human and computer strengths are rather different.



On Thu, 10 Mar 2016, uurtamo . wrote:


If that's the case, then they should be able to give opinions on best first 
moves, best first two move combos, and best first three move combos. That'd
be interesting to see. (Top 10 or so of each).

s.

On Mar 10, 2016 12:37 PM, "Sorin Gherman"  > wrote:

  From reading their article, AlphaGo makes no difference at all between 
start, middle and endgame.
  Just like any other position, the empty (or almost empty, or almost full) 
board is just another game position in which it chooses (one of)
  the most promising moves in order to maximize her chance of 

Re: [Computer-go] Finding Alphago's Weaknesses

[Jim O'Flaherty]

I think we are going to see a case of human professionals having drifted
into a local optima in at least three areas:
  1) Early training around openings is so ingrained in their acquiring
their skill (optimal neural plasticity window), there has been very little
new discovery around the first third of the game with almost all
professionals relying fairly strongly on the already time tested josekis -
AIs can use reading to explore closer and closer to the start of a game
using less and less automatic patterns thereby confusing humans who have
memorized those patterns
  2) The middle of the board is so high in reading complexity, there has
been little investment to figure out how to leverage it until mid game as
it has been more expedient to focus on the corners and edges - AIs are
going to get faster, better and deeper at reading through and then
intentionally generating complexity
  3) As a human's cognition tires, the probability of reading errors rises
non-linearly which increases the probability of late mid-game and end game
errors - I think AlphaGo has already progressed pretty far in the end game

I'd consider these the three primary general vulnerabilities of human Go
playing against any future AI. Given AlphaGo's training mechanism is
actually search space exploration engine, it will slowly but surely explore
and converge on more optimal play in all three of these domains
significantly faster and cheaper than directly investing in and expending
human cognition efforts; i.e. professionals studying to do the knowledge
expansion and verification. And I think they will continue to optimize
AlphaGo's algorithms in both human and self-play.

The window where humans are going to be able to fish out a win against
AlphaGo is rapidly closing...and it may have already closed.


Other thoughts...

I think we are going to see some fascinating "discoveries" of errors in
existing very old josekis. At some point, I think we will even see one or
two new ones discovered by AIs or by humans exploiting AIs. We are going to
see some new center oriented fighting based on vastly more complex move
sequences which will result in an substantial increase in resignations at
the professional level against each other.

Said a slightly different way...even if Lee Sedol figures how how to get a
lead in a game during the opening, AlphaGo will just continue to elevate
the board complexity with each move until it is just beyond its opponent's
reading ability while staying well within it's own reading ability
constraints. IOW, complexity is now an AIs advantage. AlphaGo doesn't have
the human frailty of being nervous of a possible future mistake and then
altering its priorities by pushing winning by a higher margin as a buffer
against said future reading complexity mistake. IOW, AlphaGo is regulated
by it's algorithm's prioritizing the probability of win higher than the
amount of margin by which it could buffer for a win. What seems like a
weakness is turning out to be one hell of a strength.

Add to the fact that this kind of behavior by AlphaGo is denying it's
opponent critical information about the state of the game which is more
readily available in human-vs-human games; i.e. AlphaGo's will continue to
converge towards calmer and calmer play in the face of chaotic play. And
the calmer it becomes, the less "weakness surface area" it will have for a
human to exploit in attempting a win.

This is utterly fascinating to get to witness. I sure wish Don Daily was
still here to get to enjoy this.


On Thu, Mar 10, 2016 at 2:52 PM, Thomas Wolf  wrote:

> With at most 2x361 or so different end scores but 10^{XXX} possible
> different
> games, there are at least in the opening many moves with the same optimal
> outcome. The difference between these moves is not the guaranteed score
> (they
> are all optimal) but the difficulty to play optimal after that move. And
> the
> human and computer strengths are rather different.
>
>
> On Thu, 10 Mar 2016, uurtamo . wrote:
>
>
>> If that's the case, then they should be able to give opinions on best
>> first moves, best first two move combos, and best first three move combos.
>> That'd
>> be interesting to see. (Top 10 or so of each).
>>
>> s.
>>
>> On Mar 10, 2016 12:37 PM, "Sorin Gherman"  wrote:
>>
>>   From reading their article, AlphaGo makes no difference at all
>> between start, middle and endgame.
>>   Just like any other position, the empty (or almost empty, or almost
>> full) board is just another game position in which it chooses (one of)
>>   the most promising moves in order to maximize her chance of winning.
>>
>>   On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:
>>
>> Quick question - how, mechanically, is the opening being
>> handled by alpha go and other recent very strong programs? Giant
>> hand-entered or game-learned joseki books?
>>
>> Thanks,
>>
>> steve
>>
>>

Re: [Computer-go] Finding Alphago's Weaknesses

[Thomas Wolf]

With at most 2x361 or so different end scores but 10^{XXX} possible different
games, there are at least in the opening many moves with the same optimal
outcome. The difference between these moves is not the guaranteed score (they
are all optimal) but the difficulty to play optimal after that move. And the
human and computer strengths are rather different.

On Thu, 10 Mar 2016, uurtamo . wrote:



If that's the case, then they should be able to give opinions on best first 
moves, best first two move combos, and best first three move combos. That'd
be interesting to see. (Top 10 or so of each).

s.

On Mar 10, 2016 12:37 PM, "Sorin Gherman"  wrote:

  From reading their article, AlphaGo makes no difference at all between 
start, middle and endgame.
  Just like any other position, the empty (or almost empty, or almost full) 
board is just another game position in which it chooses (one of)
  the most promising moves in order to maximize her chance of winning.

  On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:

Quick question - how, mechanically, is the opening being handled by 
alpha go and other recent very strong programs? Giant
hand-entered or game-learned joseki books?

Thanks,

steve

On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:
  My 2 cent:

  Recent strong computer programs never loose by a few points.  
They are either
  crashed before the end game starts (because when being 
clearly behind they play more
  desperate and weaker moves because they mainly get negative 
feadback from
  their search with mostly loosing branches and risky play 
gives them the only
  winning sequences in their search) or they win by resignation 
or win
  by a few points.

  In other words, if a human player playing AlphaGo does not 
have a large
  advantage already in the middle game, then AlphaGo will win 
whether it looks
  like it or not (even to a 9p player like Michael Redmond was 
surprised
  last night about the sudden gain of a number of points by 
AlphaGo in the
  center in the end game: 4:42:10, 4:43:00, 4:43:28 in the 
video https://gogameguru.com/alphago-2/)

  In the middle and end game the reduced number of possible 
moves and the
  precise and fast counting ability of computer programs are 
superior.  In the
  game commentary of the 1st game it was mentioned that Lee 
Sedol considers the
  opening not to be his strongest part of the game.  But with 
AlphaGo playing
  top pro level even in the opening, a large advantage after 
the middle game
  might simply be impossible to reach for a human.

  About finding weakness:
  In the absense of games of AlphaGo to study it might be 
interesting to get a general idea by checking out the games
  where 7d Zen lost on KGS
  recently.

  Thomas

  On Thu, 10 Mar 2016, wing wrote:

One question is whether Lee Sedol knows about these 
weaknesses.
Another question is whether he will exploit those 
weaknesses.
Lee has a very simple style of play that seems less 
ko-oriented
than other players, and this may play into the hands of 
Alpha.

Michael Wing

   I was surprised the Lee Sedol didn't take the 
game a bit further to
   probe AlphaGo and see how it responded to 
[...complex kos, complex ko
   fights, complex sekis, complex semeais, ..., 
multiple connection
   problems, complex life and death problems] as 
ammunition for his next
   game. I think he was so astonished at being put 
into a losing
   position, he wasn't mentally prepared to put 
himself in a student's
   role again, especially to an AI...which had 
clearly played much weaker
   games just 6 months ago. I'm hopeful Lee Sedol's 
team has been some
   meta-strategy sessions where, if he finds 
himself in a losing position
   in game two, he turns it into exploring a set of 
experiments to tease
   out some of the weaknesses to be better 
exploited in the remaining
   games.

   On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek 
 wrote:

  >  On 10.03.2016 00:45, Hideki Kato wrote:
   

Re: [Computer-go] AlphaGo won the second game!

[Olivier Teytaud]

The most surprising fact, to me, is that it's possible to apply "reinforce"
on such a large scale. Reinforce is not new, but even with millions of cores
I did not expect this to be possible. I would have assumed that reinforce
would
just produce random noise when applied at such a scale :-)


On Thu, Mar 10, 2016 at 9:29 PM, Petr Baudis  wrote:

> On Thu, Mar 10, 2016 at 07:20:11PM +, Josef Moudrik wrote:
> > Yes, but they are not some random cherry picking third party; have a look
> > on the top authors of the paper - David Silver, Aja Huang, Chris
> Maddison..
>
> Also, they aren't merely wrapping engineering around existing science
> and putting existing things together, but invented several new methods
> too.  So, of course they are standing on the shoulders of giants, and
> the massive computational resources of Google had been a lot of help,
> but I'd say there is a fair amount of originality in the AlphaGo
> research, scientifically.
>
> Petr Baudis
> ___
> Computer-go mailing list
> Computer-go@computer-go.org
> http://computer-go.org/mailman/listinfo/computer-go
>



-- 
=
Olivier Teytaud, olivier.teyt...@inria.fr, TAO, LRI, UMR 8623(CNRS - Univ.
Paris-Sud),
bat 490 Univ. Paris-Sud F-91405 Orsay Cedex France
http://www.slideshare.net/teytaud
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Finding Alphago's Weaknesses

[Sorin Gherman]

For that reason I guess that AlphaGo opening style is mostly influenced by
the net that is trained on strong human games, while as the game progresses
the MC rollouts have more and more influence in choosing a move.
Is my understanding way off?
On Mar 10, 2016 12:40 PM, "Thomas Wolf"  wrote:

> But at the start of the game the statistical learning of infinitessimal
> advantages of one opening move compared to another opening move is less
> efficient than the learning done in the middle and end game.
>
> On Thu, 10 Mar 2016, Sorin Gherman wrote:
>
>
>> From reading their article, AlphaGo makes no difference at all between
>> start, middle and endgame.
>> Just like any other position, the empty (or almost empty, or almost full)
>> board is just another game position in which it chooses (one of) the most
>> promising moves in order to maximize her chance of winning.
>>
>> On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:
>>
>>   Quick question - how, mechanically, is the opening being handled by
>> alpha go and other recent very strong programs? Giant hand-entered or
>>   game-learned joseki books?
>>
>>   Thanks,
>>
>>   steve
>>
>>   On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:
>> My 2 cent:
>>
>> Recent strong computer programs never loose by a few points.
>> They are either
>> crashed before the end game starts (because when being
>> clearly behind they play more
>> desperate and weaker moves because they mainly get negative
>> feadback from
>> their search with mostly loosing branches and risky play
>> gives them the only
>> winning sequences in their search) or they win by resignation
>> or win
>> by a few points.
>>
>> In other words, if a human player playing AlphaGo does not
>> have a large
>> advantage already in the middle game, then AlphaGo will win
>> whether it looks
>> like it or not (even to a 9p player like Michael Redmond was
>> surprised
>> last night about the sudden gain of a number of points by
>> AlphaGo in the
>> center in the end game: 4:42:10, 4:43:00, 4:43:28 in the
>> video https://gogameguru.com/alphago-2/)
>>
>> In the middle and end game the reduced number of possible
>> moves and the
>> precise and fast counting ability of computer programs are
>> superior.  In the
>> game commentary of the 1st game it was mentioned that Lee
>> Sedol considers the
>> opening not to be his strongest part of the game.  But with
>> AlphaGo playing
>> top pro level even in the opening, a large advantage after
>> the middle game
>> might simply be impossible to reach for a human.
>>
>> About finding weakness:
>> In the absense of games of AlphaGo to study it might be
>> interesting to get a general idea by checking out the games where 7d Zen
>> lost on KGS
>> recently.
>>
>> Thomas
>>
>> On Thu, 10 Mar 2016, wing wrote:
>>
>>   One question is whether Lee Sedol knows about these
>> weaknesses.
>>   Another question is whether he will exploit those
>> weaknesses.
>>   Lee has a very simple style of play that seems less
>> ko-oriented
>>   than other players, and this may play into the hands of
>> Alpha.
>>
>>   Michael Wing
>>
>>  I was surprised the Lee Sedol didn't take the
>> game a bit further to
>>  probe AlphaGo and see how it responded to
>> [...complex kos, complex ko
>>  fights, complex sekis, complex semeais,
>> ..., multiple connection
>>  problems, complex life and death problems] as
>> ammunition for his next
>>  game. I think he was so astonished at being put
>> into a losing
>>  position, he wasn't mentally prepared to put
>> himself in a student's
>>  role again, especially to an AI...which had
>> clearly played much weaker
>>  games just 6 months ago. I'm hopeful Lee Sedol's
>> team has been some
>>  meta-strategy sessions where, if he finds
>> himself in a losing position
>>  in game two, he turns it into exploring a set of
>> experiments to tease
>>  out some of the weaknesses to be better
>> exploited in the remaining
>>  games.
>>
>>  On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek <
>> jas...@snafu.de> wrote:
>>
>> >  On 10.03.2016 00:45, Hideki Kato wrote:
>> > > >  such as solving complex semeai's and
>> double-ko's, aren't solved yet.
>> > >  To find out Alphago's 

Re: [Computer-go] Finding Alphago's Weaknesses

[uurtamo .]

If that's the case, then they should be able to give opinions on best first
moves, best first two move combos, and best first three move combos. That'd
be interesting to see. (Top 10 or so of each).

s.
On Mar 10, 2016 12:37 PM, "Sorin Gherman"  wrote:

> From reading their article, AlphaGo makes no difference at all between
> start, middle and endgame.
> Just like any other position, the empty (or almost empty, or almost full)
> board is just another game position in which it chooses (one of) the most
> promising moves in order to maximize her chance of winning.
> On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:
>
>> Quick question - how, mechanically, is the opening being handled by alpha
>> go and other recent very strong programs? Giant hand-entered or
>> game-learned joseki books?
>>
>> Thanks,
>>
>> steve
>> On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:
>>
>>> My 2 cent:
>>>
>>> Recent strong computer programs never loose by a few points.  They are
>>> either
>>> crashed before the end game starts (because when being clearly behind
>>> they play more
>>> desperate and weaker moves because they mainly get negative feadback from
>>> their search with mostly loosing branches and risky play gives them the
>>> only
>>> winning sequences in their search) or they win by resignation or win
>>> by a few points.
>>>
>>> In other words, if a human player playing AlphaGo does not have a large
>>> advantage already in the middle game, then AlphaGo will win whether it
>>> looks
>>> like it or not (even to a 9p player like Michael Redmond was surprised
>>> last night about the sudden gain of a number of points by AlphaGo in the
>>> center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video
>>> https://gogameguru.com/alphago-2/)
>>>
>>> In the middle and end game the reduced number of possible moves and the
>>> precise and fast counting ability of computer programs are superior.  In
>>> the
>>> game commentary of the 1st game it was mentioned that Lee Sedol
>>> considers the
>>> opening not to be his strongest part of the game.  But with AlphaGo
>>> playing
>>> top pro level even in the opening, a large advantage after the middle
>>> game
>>> might simply be impossible to reach for a human.
>>>
>>> About finding weakness:
>>> In the absense of games of AlphaGo to study it might be interesting to
>>> get a general idea by checking out the games where 7d Zen lost on KGS
>>> recently.
>>>
>>> Thomas
>>>
>>> On Thu, 10 Mar 2016, wing wrote:
>>>
>>> One question is whether Lee Sedol knows about these weaknesses.
 Another question is whether he will exploit those weaknesses.
 Lee has a very simple style of play that seems less ko-oriented
 than other players, and this may play into the hands of Alpha.

 Michael Wing

  I was surprised the Lee Sedol didn't take the game a bit further to
>  probe AlphaGo and see how it responded to [...complex kos, complex ko
>  fights, complex sekis, complex semeais, ..., multiple connection
>  problems, complex life and death problems] as ammunition for his next
>  game. I think he was so astonished at being put into a losing
>  position, he wasn't mentally prepared to put himself in a student's
>  role again, especially to an AI...which had clearly played much weaker
>  games just 6 months ago. I'm hopeful Lee Sedol's team has been some
>  meta-strategy sessions where, if he finds himself in a losing position
>  in game two, he turns it into exploring a set of experiments to tease
>  out some of the weaknesses to be better exploited in the remaining
>  games.
>
>  On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek 
> wrote:
>
> >  On 10.03.2016 00:45, Hideki Kato wrote:
> > > >  such as solving complex semeai's and double-ko's, aren't solved
> yet.
> > >  To find out Alphago's weaknesses, there can be, in particular,
> > >  - this match
> >  - careful analysis of its games
> >  - Alphago playing on artificial problem positions incl. complex
> kos, >  complex ko fights, complex sekis, complex semeais, complex
> endgames, >  multiple connection problems, complex life and death problems
> (such as >  Igo Hatsu Yoron 120) etc., and then theoretical analysis of
> such play
> >  - semantic verification of the program code and interface
> >  - theoretical study of the used theory and the generated dynamic
> data >  (structures)
> > >  --
> >  robert jasiek
> >  ___
> >  Computer-go mailing list
> >  Computer-go@computer-go.org
> >  http://computer-go.org/mailman/listinfo/computer-go [1]
>
>
>
>  Links:
>  --
>  [1] http://computer-go.org/mailman/listinfo/computer-go
>
>  ___
>  Computer-go mailing list
>  

Re: [Computer-go] Finding Alphago's Weaknesses

[Thomas Wolf]

But at the start of the game the statistical learning of infinitessimal
advantages of one opening move compared to another opening move is less
efficient than the learning done in the middle and end game.

On Thu, 10 Mar 2016, Sorin Gherman wrote:



From reading their article, AlphaGo makes no difference at all between start, 
middle and endgame.
Just like any other position, the empty (or almost empty, or almost full) board 
is just another game position in which it chooses (one of) the most
promising moves in order to maximize her chance of winning.

On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:

  Quick question - how, mechanically, is the opening being handled by alpha 
go and other recent very strong programs? Giant hand-entered or
  game-learned joseki books?

  Thanks,

  steve

  On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:
My 2 cent:

Recent strong computer programs never loose by a few points.  They 
are either
crashed before the end game starts (because when being clearly 
behind they play more
desperate and weaker moves because they mainly get negative 
feadback from
their search with mostly loosing branches and risky play gives them 
the only
winning sequences in their search) or they win by resignation or win
by a few points.

In other words, if a human player playing AlphaGo does not have a 
large
advantage already in the middle game, then AlphaGo will win whether 
it looks
like it or not (even to a 9p player like Michael Redmond was 
surprised
last night about the sudden gain of a number of points by AlphaGo 
in the
center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video 
https://gogameguru.com/alphago-2/)

In the middle and end game the reduced number of possible moves and 
the
precise and fast counting ability of computer programs are 
superior.  In the
game commentary of the 1st game it was mentioned that Lee Sedol 
considers the
opening not to be his strongest part of the game.  But with AlphaGo 
playing
top pro level even in the opening, a large advantage after the 
middle game
might simply be impossible to reach for a human.

About finding weakness:
In the absense of games of AlphaGo to study it might be interesting 
to get a general idea by checking out the games where 7d Zen
lost on KGS
recently.

Thomas

On Thu, 10 Mar 2016, wing wrote:

  One question is whether Lee Sedol knows about these 
weaknesses.
  Another question is whether he will exploit those weaknesses.
  Lee has a very simple style of play that seems less 
ko-oriented
  than other players, and this may play into the hands of Alpha.

  Michael Wing

 I was surprised the Lee Sedol didn't take the game a 
bit further to
 probe AlphaGo and see how it responded to [...complex 
kos, complex ko
 fights, complex sekis, complex semeais, ..., multiple 
connection
 problems, complex life and death problems] as 
ammunition for his next
 game. I think he was so astonished at being put into a 
losing
 position, he wasn't mentally prepared to put himself 
in a student's
 role again, especially to an AI...which had clearly 
played much weaker
 games just 6 months ago. I'm hopeful Lee Sedol's team 
has been some
 meta-strategy sessions where, if he finds himself in a 
losing position
 in game two, he turns it into exploring a set of 
experiments to tease
 out some of the weaknesses to be better exploited in 
the remaining
 games.

 On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek 
 wrote:

>  On 10.03.2016 00:45, Hideki Kato wrote:
> > >  such as solving complex semeai's and 
double-ko's, aren't solved yet.
> >  To find out Alphago's weaknesses, there can be, in 
particular,
> >  - this match
>  - careful analysis of its games
>  - Alphago playing on artificial problem positions incl. 
complex kos, >  complex ko fights, complex
sekis, complex semeais, complex endgames, >  multiple 
connection problems, complex life and death
problems (such as >  Igo Hatsu Yoron 120) etc., and 
then theoretical analysis of such play
>  - semantic verification of the program code and 

Re: [Computer-go] Finding Alphago's Weaknesses

[Sorin Gherman]

>From reading their article, AlphaGo makes no difference at all between
start, middle and endgame.
Just like any other position, the empty (or almost empty, or almost full)
board is just another game position in which it chooses (one of) the most
promising moves in order to maximize her chance of winning.
On Mar 10, 2016 12:31 PM, "uurtamo ."  wrote:

> Quick question - how, mechanically, is the opening being handled by alpha
> go and other recent very strong programs? Giant hand-entered or
> game-learned joseki books?
>
> Thanks,
>
> steve
> On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:
>
>> My 2 cent:
>>
>> Recent strong computer programs never loose by a few points.  They are
>> either
>> crashed before the end game starts (because when being clearly behind
>> they play more
>> desperate and weaker moves because they mainly get negative feadback from
>> their search with mostly loosing branches and risky play gives them the
>> only
>> winning sequences in their search) or they win by resignation or win
>> by a few points.
>>
>> In other words, if a human player playing AlphaGo does not have a large
>> advantage already in the middle game, then AlphaGo will win whether it
>> looks
>> like it or not (even to a 9p player like Michael Redmond was surprised
>> last night about the sudden gain of a number of points by AlphaGo in the
>> center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video
>> https://gogameguru.com/alphago-2/)
>>
>> In the middle and end game the reduced number of possible moves and the
>> precise and fast counting ability of computer programs are superior.  In
>> the
>> game commentary of the 1st game it was mentioned that Lee Sedol considers
>> the
>> opening not to be his strongest part of the game.  But with AlphaGo
>> playing
>> top pro level even in the opening, a large advantage after the middle game
>> might simply be impossible to reach for a human.
>>
>> About finding weakness:
>> In the absense of games of AlphaGo to study it might be interesting to
>> get a general idea by checking out the games where 7d Zen lost on KGS
>> recently.
>>
>> Thomas
>>
>> On Thu, 10 Mar 2016, wing wrote:
>>
>> One question is whether Lee Sedol knows about these weaknesses.
>>> Another question is whether he will exploit those weaknesses.
>>> Lee has a very simple style of play that seems less ko-oriented
>>> than other players, and this may play into the hands of Alpha.
>>>
>>> Michael Wing
>>>
>>>  I was surprised the Lee Sedol didn't take the game a bit further to
  probe AlphaGo and see how it responded to [...complex kos, complex ko
  fights, complex sekis, complex semeais, ..., multiple connection
  problems, complex life and death problems] as ammunition for his next
  game. I think he was so astonished at being put into a losing
  position, he wasn't mentally prepared to put himself in a student's
  role again, especially to an AI...which had clearly played much weaker
  games just 6 months ago. I'm hopeful Lee Sedol's team has been some
  meta-strategy sessions where, if he finds himself in a losing position
  in game two, he turns it into exploring a set of experiments to tease
  out some of the weaknesses to be better exploited in the remaining
  games.

  On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek 
 wrote:

 >  On 10.03.2016 00:45, Hideki Kato wrote:
 > > >  such as solving complex semeai's and double-ko's, aren't solved
 yet.
 > >  To find out Alphago's weaknesses, there can be, in particular,
 > >  - this match
 >  - careful analysis of its games
 >  - Alphago playing on artificial problem positions incl. complex kos,
 >  complex ko fights, complex sekis, complex semeais, complex endgames, >
 multiple connection problems, complex life and death problems (such as >
 Igo Hatsu Yoron 120) etc., and then theoretical analysis of such play
 >  - semantic verification of the program code and interface
 >  - theoretical study of the used theory and the generated dynamic
 data >  (structures)
 > >  --
 >  robert jasiek
 >  ___
 >  Computer-go mailing list
 >  Computer-go@computer-go.org
 >  http://computer-go.org/mailman/listinfo/computer-go [1]



  Links:
  --
  [1] 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
>>>
>>
>> ___
>> Computer-go mailing list
>> Computer-go@computer-go.org
>> 

Re: [Computer-go] Finding Alphago's Weaknesses

[uurtamo .]

Quick question - how, mechanically, is the opening being handled by alpha
go and other recent very strong programs? Giant hand-entered or
game-learned joseki books?

Thanks,

steve
On Mar 10, 2016 12:23 PM, "Thomas Wolf"  wrote:

> My 2 cent:
>
> Recent strong computer programs never loose by a few points.  They are
> either
> crashed before the end game starts (because when being clearly behind they
> play more
> desperate and weaker moves because they mainly get negative feadback from
> their search with mostly loosing branches and risky play gives them the
> only
> winning sequences in their search) or they win by resignation or win
> by a few points.
>
> In other words, if a human player playing AlphaGo does not have a large
> advantage already in the middle game, then AlphaGo will win whether it
> looks
> like it or not (even to a 9p player like Michael Redmond was surprised
> last night about the sudden gain of a number of points by AlphaGo in the
> center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video
> https://gogameguru.com/alphago-2/)
>
> In the middle and end game the reduced number of possible moves and the
> precise and fast counting ability of computer programs are superior.  In
> the
> game commentary of the 1st game it was mentioned that Lee Sedol considers
> the
> opening not to be his strongest part of the game.  But with AlphaGo playing
> top pro level even in the opening, a large advantage after the middle game
> might simply be impossible to reach for a human.
>
> About finding weakness:
> In the absense of games of AlphaGo to study it might be interesting to get
> a general idea by checking out the games where 7d Zen lost on KGS
> recently.
>
> Thomas
>
> On Thu, 10 Mar 2016, wing wrote:
>
> One question is whether Lee Sedol knows about these weaknesses.
>> Another question is whether he will exploit those weaknesses.
>> Lee has a very simple style of play that seems less ko-oriented
>> than other players, and this may play into the hands of Alpha.
>>
>> Michael Wing
>>
>>  I was surprised the Lee Sedol didn't take the game a bit further to
>>>  probe AlphaGo and see how it responded to [...complex kos, complex ko
>>>  fights, complex sekis, complex semeais, ..., multiple connection
>>>  problems, complex life and death problems] as ammunition for his next
>>>  game. I think he was so astonished at being put into a losing
>>>  position, he wasn't mentally prepared to put himself in a student's
>>>  role again, especially to an AI...which had clearly played much weaker
>>>  games just 6 months ago. I'm hopeful Lee Sedol's team has been some
>>>  meta-strategy sessions where, if he finds himself in a losing position
>>>  in game two, he turns it into exploring a set of experiments to tease
>>>  out some of the weaknesses to be better exploited in the remaining
>>>  games.
>>>
>>>  On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  wrote:
>>>
>>> >  On 10.03.2016 00:45, Hideki Kato wrote:
>>> > > >  such as solving complex semeai's and double-ko's, aren't solved
>>> yet.
>>> > >  To find out Alphago's weaknesses, there can be, in particular,
>>> > >  - this match
>>> >  - careful analysis of its games
>>> >  - Alphago playing on artificial problem positions incl. complex kos,
>>> >  complex ko fights, complex sekis, complex semeais, complex endgames, >
>>> multiple connection problems, complex life and death problems (such as >
>>> Igo Hatsu Yoron 120) etc., and then theoretical analysis of such play
>>> >  - semantic verification of the program code and interface
>>> >  - theoretical study of the used theory and the generated dynamic data
>>> >  (structures)
>>> > >  --
>>> >  robert jasiek
>>> >  ___
>>> >  Computer-go mailing list
>>> >  Computer-go@computer-go.org
>>> >  http://computer-go.org/mailman/listinfo/computer-go [1]
>>>
>>>
>>>
>>>  Links:
>>>  --
>>>  [1] 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
>>
>
> ___
> 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

Re: [Computer-go] Finding Alphago's Weaknesses

[Thomas Wolf]

My 2 cent:

Recent strong computer programs never loose by a few points.  They are either
crashed before the end game starts (because when being clearly behind they play 
more
desperate and weaker moves because they mainly get negative feadback from
their search with mostly loosing branches and risky play gives them the only
winning sequences in their search) or they win by resignation or win
by a few points.

In other words, if a human player playing AlphaGo does not have a large
advantage already in the middle game, then AlphaGo will win whether it looks
like it or not (even to a 9p player like Michael Redmond was surprised
last night about the sudden gain of a number of points by AlphaGo in the
center in the end game: 4:42:10, 4:43:00, 4:43:28 in the video 
https://gogameguru.com/alphago-2/)


In the middle and end game the reduced number of possible moves and the
precise and fast counting ability of computer programs are superior.  In the
game commentary of the 1st game it was mentioned that Lee Sedol considers the
opening not to be his strongest part of the game.  But with AlphaGo playing
top pro level even in the opening, a large advantage after the middle game
might simply be impossible to reach for a human.

About finding weakness:
In the absense of games of AlphaGo to study it might be interesting 
to get a general idea by checking out the games where 7d Zen lost on KGS

recently.

Thomas

On Thu, 10 Mar 2016, wing wrote:


One question is whether Lee Sedol knows about these weaknesses.
Another question is whether he will exploit those weaknesses.
Lee has a very simple style of play that seems less ko-oriented
than other players, and this may play into the hands of Alpha.

Michael Wing


 I was surprised the Lee Sedol didn't take the game a bit further to
 probe AlphaGo and see how it responded to [...complex kos, complex ko
 fights, complex sekis, complex semeais, ..., multiple connection
 problems, complex life and death problems] as ammunition for his next
 game. I think he was so astonished at being put into a losing
 position, he wasn't mentally prepared to put himself in a student's
 role again, especially to an AI...which had clearly played much weaker
 games just 6 months ago. I'm hopeful Lee Sedol's team has been some
 meta-strategy sessions where, if he finds himself in a losing position
 in game two, he turns it into exploring a set of experiments to tease
 out some of the weaknesses to be better exploited in the remaining
 games.

 On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  wrote:

>  On 10.03.2016 00:45, Hideki Kato wrote:
> 
> >  such as solving complex semeai's and double-ko's, aren't solved yet.
> 
>  To find out Alphago's weaknesses, there can be, in particular,
> 
>  - this match

>  - careful analysis of its games
>  - Alphago playing on artificial problem positions incl. complex kos, 
>  complex ko fights, complex sekis, complex semeais, complex endgames, 
>  multiple connection problems, complex life and death problems (such as 
>  Igo Hatsu Yoron 120) etc., and then theoretical analysis of such play

>  - semantic verification of the program code and interface
>  - theoretical study of the used theory and the generated dynamic data 
>  (structures)
> 
>  --

>  robert jasiek
>  ___
>  Computer-go mailing list
>  Computer-go@computer-go.org
>  http://computer-go.org/mailman/listinfo/computer-go [1]



 Links:
 --
 [1] 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
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Finding Alphago's Weaknesses

[Sorin Gherman]

I doubt that the human-perceived weaknesses in AlphaGo are really
weaknesses - after the second game it seems more like AlphaGo has
"everything under control".
Professional players will still find moves to criticize, but I want to see
proof that any such move would change the fate of the game :-)

Sorin Gherman

On Thu, Mar 10, 2016 at 10:13 AM, wing  wrote:

> One question is whether Lee Sedol knows about these weaknesses.
> Another question is whether he will exploit those weaknesses.
> Lee has a very simple style of play that seems less ko-oriented
> than other players, and this may play into the hands of Alpha.
>
> Michael Wing
>
> I was surprised the Lee Sedol didn't take the game a bit further to
>> probe AlphaGo and see how it responded to [...complex kos, complex ko
>> fights, complex sekis, complex semeais, ..., multiple connection
>> problems, complex life and death problems] as ammunition for his next
>> game. I think he was so astonished at being put into a losing
>> position, he wasn't mentally prepared to put himself in a student's
>> role again, especially to an AI...which had clearly played much weaker
>> games just 6 months ago. I'm hopeful Lee Sedol's team has been some
>> meta-strategy sessions where, if he finds himself in a losing position
>> in game two, he turns it into exploring a set of experiments to tease
>> out some of the weaknesses to be better exploited in the remaining
>> games.
>>
>> On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  wrote:
>>
>> On 10.03.2016 00:45, Hideki Kato wrote:
>>>
>>> such as solving complex semeai's and double-ko's, aren't solved yet.

>>>
>>> To find out Alphago's weaknesses, there can be, in particular,
>>>
>>> - this match
>>> - careful analysis of its games
>>> - Alphago playing on artificial problem positions incl. complex kos,
>>> complex ko fights, complex sekis, complex semeais, complex endgames,
>>> multiple connection problems, complex life and death problems (such as Igo
>>> Hatsu Yoron 120) etc., and then theoretical analysis of such play
>>> - semantic verification of the program code and interface
>>> - theoretical study of the used theory and the generated dynamic data
>>> (structures)
>>>
>>> --
>>> robert jasiek
>>> ___
>>> Computer-go mailing list
>>> Computer-go@computer-go.org
>>> http://computer-go.org/mailman/listinfo/computer-go [1]
>>>
>>
>>
>>
>> Links:
>> --
>> [1] 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
>
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] AlphaGo won the second game!

[Josef Moudrik]

Yes, but they are not some random cherry picking third party; have a look
on the top authors of the paper - David Silver, Aja Huang, Chris Maddison..

Regards,
Josef

Dne čt 10. 3. 2016 19:47 uživatel Lukas van de Wiel <
lukas.drinkt.t...@gmail.com> napsal:

> The same here, with other people having built the foundations of go AIs,
> and going from neural networks to MCTS, and now back-ish again...
> But that is how is how science works. Eventually these two wins are the
> reward of decades of culminated work by many people working on go AI.
> AlphaGo is the Cherry on the enormous cake.
>
> On Fri, Mar 11, 2016 at 7:43 AM, Marco Scheurer  wrote:
>
>> Congratulations indeed.
>>
>> Although I must admit I have mixed feelings about this, that it is
>> Google, using enormous resources, that got there first.
>>
>> marco
>>
>> On 10 Mar 2016, at 19:38, Lukas van de Wiel 
>> wrote:
>>
>> Congratz to AlphaGo, once more!
>> This is getting scary! :-)
>>
>> Lukas
>>
>> On Fri, Mar 11, 2016 at 12:40 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
>> wrote:
>>
>>> Hello,
>>>
>>>
>>> Von: "Erik van der Werf" 
>>> > Very impressive results so far!
>>>
>>> indeed, almost unbelievable.
>>>
>>>
>>> > If it's going to be a clean sweep, I hope we will get to see some
>>> handicap games :-)
>>>
>>>
>>> I have another proposal, IF a clean sweep will happen:
>>> There was an announcement three days ago by a Chinese group that
>>> they are developing a strong go bot and want to challenge
>>> No. 1 player Ke Jie (still in 2016).
>>> The winner of that match might challenge AlphaGo.
>>>
>>> Ingo.
>>>
>>>
>>> http://senseis.xmp.net/?KeJie
>>>
>>> ___
>>> 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
>>
>
> ___
> 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

Re: [Computer-go] Finding Alphago's Weaknesses

[Robert Jasiek]

On 10.03.2016 16:48, Darren Cook wrote:

 in game 2, black 43 and 45 were described as "a little
heavy". It did seem (to my weak eyes) to turn out poorly. I'm curious if
this was a real mistake by AlphaGo, or if it was already happy it was
leading, and this was the one it felt led to the safest win?


In human terms, it was a combination of: limitation of the expansion 
potential of the white left side, shinogi, sente and developing the 
potential of the upper side including its center potential. Ugly and 
marvellous strategy of simplifying the game (same: reduction of the 
right side in sente) and creating a winning position by robbing White of 
every option of creating significant new territory regions / expansions.


--
robert jasiek
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] AlphaGo won the second game!

[Lukas van de Wiel]

The same here, with other people having built the foundations of go AIs,
and going from neural networks to MCTS, and now back-ish again...
But that is how is how science works. Eventually these two wins are the
reward of decades of culminated work by many people working on go AI.
AlphaGo is the Cherry on the enormous cake.

On Fri, Mar 11, 2016 at 7:43 AM, Marco Scheurer  wrote:

> Congratulations indeed.
>
> Although I must admit I have mixed feelings about this, that it is Google,
> using enormous resources, that got there first.
>
> marco
>
> On 10 Mar 2016, at 19:38, Lukas van de Wiel 
> wrote:
>
> Congratz to AlphaGo, once more!
> This is getting scary! :-)
>
> Lukas
>
> On Fri, Mar 11, 2016 at 12:40 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
> wrote:
>
>> Hello,
>>
>>
>> Von: "Erik van der Werf" 
>> > Very impressive results so far!
>>
>> indeed, almost unbelievable.
>>
>>
>> > If it's going to be a clean sweep, I hope we will get to see some
>> handicap games :-)
>>
>>
>> I have another proposal, IF a clean sweep will happen:
>> There was an announcement three days ago by a Chinese group that
>> they are developing a strong go bot and want to challenge
>> No. 1 player Ke Jie (still in 2016).
>> The winner of that match might challenge AlphaGo.
>>
>> Ingo.
>>
>>
>> http://senseis.xmp.net/?KeJie
>>
>> ___
>> 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
>
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] AlphaGo won the second game!

[Marco Scheurer]

Congratulations indeed. 

Although I must admit I have mixed feelings about this, that it is Google, 
using enormous resources, that got there first. 

marco

> On 10 Mar 2016, at 19:38, Lukas van de Wiel  
> wrote:
> 
> Congratz to AlphaGo, once more!
> This is getting scary! :-)
> 
> Lukas
> 
>> On Fri, Mar 11, 2016 at 12:40 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de> 
>> wrote:
>> Hello,
>>  
>> 
>> Von: "Erik van der Werf" 
>> > Very impressive results so far!
>>  
>> indeed, almost unbelievable.
>> 
>> 
>> > If it's going to be a clean sweep, I hope we will get to see some handicap 
>> > games :-)
>> 
>> 
>> I have another proposal, IF a clean sweep will happen:
>> There was an announcement three days ago by a Chinese group that
>> they are developing a strong go bot and want to challenge
>> No. 1 player Ke Jie (still in 2016).
>> The winner of that match might challenge AlphaGo.
>> 
>> Ingo.
>> 
>> 
>> http://senseis.xmp.net/?KeJie
>> 
>> ___
>> 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

Re: [Computer-go] AlphaGo won the second game!

[Lukas van de Wiel]

Congratz to AlphaGo, once more!
This is getting scary! :-)

Lukas

On Fri, Mar 11, 2016 at 12:40 AM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
wrote:

> Hello,
>
>
> Von: "Erik van der Werf" 
> > Very impressive results so far!
>
> indeed, almost unbelievable.
>
>
> > If it's going to be a clean sweep, I hope we will get to see some
> handicap games :-)
>
>
> I have another proposal, IF a clean sweep will happen:
> There was an announcement three days ago by a Chinese group that
> they are developing a strong go bot and want to challenge
> No. 1 player Ke Jie (still in 2016).
> The winner of that match might challenge AlphaGo.
>
> Ingo.
>
>
> http://senseis.xmp.net/?KeJie
>
> ___
> 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

Re: [Computer-go] Finding Alphago's Weaknesses

[wing]

One question is whether Lee Sedol knows about these weaknesses.
Another question is whether he will exploit those weaknesses.
Lee has a very simple style of play that seems less ko-oriented
than other players, and this may play into the hands of Alpha.

Michael Wing


I was surprised the Lee Sedol didn't take the game a bit further to
probe AlphaGo and see how it responded to [...complex kos, complex ko
fights, complex sekis, complex semeais, ..., multiple connection
problems, complex life and death problems] as ammunition for his next
game. I think he was so astonished at being put into a losing
position, he wasn't mentally prepared to put himself in a student's
role again, especially to an AI...which had clearly played much 
weaker

games just 6 months ago. I'm hopeful Lee Sedol's team has been some
meta-strategy sessions where, if he finds himself in a losing 
position

in game two, he turns it into exploring a set of experiments to tease
out some of the weaknesses to be better exploited in the remaining
games.

On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  
wrote:



On 10.03.2016 00:45, Hideki Kato wrote:

such as solving complex semeai's and double-ko's, aren't solved 
yet.


To find out Alphago's weaknesses, there can be, in particular,

- this match
- careful analysis of its games
- Alphago playing on artificial problem positions incl. complex kos, 
complex ko fights, complex sekis, complex semeais, complex endgames, 
multiple connection problems, complex life and death problems (such as 
Igo Hatsu Yoron 120) etc., and then theoretical analysis of such play

- semantic verification of the program code and interface
- theoretical study of the used theory and the generated dynamic 
data (structures)


--
robert jasiek
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go [1]




Links:
--
[1] 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

Re: [Computer-go] Finding Alphago's Weaknesses

[Darren Cook]

> In fact in game 2, white 172 was described [1] as the losing move,
> because it would have started a ko. ...

"would have started a ko" --> "should have instead started a ko"

___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] Finding Alphago's Weaknesses

[Jim O'Flaherty]

I was surprised the Lee Sedol didn't take the game a bit further to probe
AlphaGo and see how it responded to [...complex kos, complex ko fights,
complex sekis, complex semeais, ..., multiple connection problems, complex
life and death problems] as ammunition for his next game. I think he was so
astonished at being put into a losing position, he wasn't mentally prepared
to put himself in a student's role again, especially to an AI...which had
clearly played much weaker games just 6 months ago. I'm hopeful Lee Sedol's
team has been some meta-strategy sessions where, if he finds himself in a
losing position in game two, he turns it into exploring a set of
experiments to tease out some of the weaknesses to be better exploited in
the remaining games.

On Thu, Mar 10, 2016 at 8:16 AM, Robert Jasiek  wrote:

> On 10.03.2016 00:45, Hideki Kato wrote:
>
>> such as solving complex semeai's and double-ko's, aren't solved yet.
>>
>
> To find out Alphago's weaknesses, there can be, in particular,
>
> - this match
> - careful analysis of its games
> - Alphago playing on artificial problem positions incl. complex kos,
> complex ko fights, complex sekis, complex semeais, complex endgames,
> multiple connection problems, complex life and death problems (such as Igo
> Hatsu Yoron 120) etc., and then theoretical analysis of such play
> - semantic verification of the program code and interface
> - theoretical study of the used theory and the generated dynamic data
> (structures)
>
> --
> robert jasiek
> ___
> 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] Finding Alphago's Weaknesses

[Robert Jasiek]

On 10.03.2016 00:45, Hideki Kato wrote:

such as solving complex semeai's and double-ko's, aren't solved yet.


To find out Alphago's weaknesses, there can be, in particular,

- this match
- careful analysis of its games
- Alphago playing on artificial problem positions incl. complex kos, 
complex ko fights, complex sekis, complex semeais, complex endgames, 
multiple connection problems, complex life and death problems (such as 
Igo Hatsu Yoron 120) etc., and then theoretical analysis of such play

- semantic verification of the program code and interface
- theoretical study of the used theory and the generated dynamic data 
(structures)


--
robert jasiek
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] AlphaGo won the second game!

[Ingo Althöfer]

Hello, 
 

Von: "Erik van der Werf" 
> Very impressive results so far!
 
indeed, almost unbelievable.


> If it's going to be a clean sweep, I hope we will get to see some handicap 
> games :-)


I have another proposal, IF a clean sweep will happen:
There was an announcement three days ago by a Chinese group that
they are developing a strong go bot and want to challenge
No. 1 player Ke Jie (still in 2016). 
The winner of that match might challenge AlphaGo.

Ingo.


http://senseis.xmp.net/?KeJie

___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] AlphaGo won the second game!

[Erik van der Werf]

Very impressive results so far!

If it's going to be a clean sweep, I hope we will get to see some handicap
games :-)

Erik


On Thu, Mar 10, 2016 at 12:04 PM, Petr Baudis  wrote:

> In the press conference (https://youtu.be/l-GsfyVCBu0?t=5h40m00s), Lee
> Sedol said that while he saw some questionable moves by AlphaGo in the
> first game, he feels that the second game was a near-perfect play by
> AlphaGo and he did not feel ahead at any point of the game.
>
> On Thu, Mar 10, 2016 at 12:44:23PM +0200, Petri Pitkanen wrote:
> > This time I think game was tougher. Though too weak to judge. At the end
> > sacrifice a fistfull stones does puzzle me, but again way too weak to
> > analyze it.
> >
> > It seem Lee Sedol is lucky if he wins a game
> >
> > 2016-03-10 12:39 GMT+02:00 Petr Baudis :
> >
> > > On Wed, Mar 09, 2016 at 09:05:48PM -0800, David Fotland wrote:
> > > > I predicted Sedol would be shocked.  I'm still routing for Sedol.
> From
> > > Scientific American interview...
> > > >
> > > > Schaeffer and Fotland still predict Sedol will win the match. “I
> think
> > > the pro will win,” Fotland says, “But I think the pro will be shocked
> at
> > > how strong the program is.”
> > >
> > > In that case it's time for Lee Sedol to start working hard on turning
> > > this match around, because AlphaGo won the second game too! :)
> > >
> > > Petr Baudis
> > > ___
> > > 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
>
>
> --
> Petr Baudis
> If you have good ideas, good data and fast computers,
> you can do almost anything. -- Geoffrey Hinton
> ___
> 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

Re: [Computer-go] AlphaGo won the second game!

[Petr Baudis]

In the press conference (https://youtu.be/l-GsfyVCBu0?t=5h40m00s), Lee
Sedol said that while he saw some questionable moves by AlphaGo in the
first game, he feels that the second game was a near-perfect play by
AlphaGo and he did not feel ahead at any point of the game.

On Thu, Mar 10, 2016 at 12:44:23PM +0200, Petri Pitkanen wrote:
> This time I think game was tougher. Though too weak to judge. At the end
> sacrifice a fistfull stones does puzzle me, but again way too weak to
> analyze it.
> 
> It seem Lee Sedol is lucky if he wins a game
> 
> 2016-03-10 12:39 GMT+02:00 Petr Baudis :
> 
> > On Wed, Mar 09, 2016 at 09:05:48PM -0800, David Fotland wrote:
> > > I predicted Sedol would be shocked.  I'm still routing for Sedol.  From
> > Scientific American interview...
> > >
> > > Schaeffer and Fotland still predict Sedol will win the match. “I think
> > the pro will win,” Fotland says, “But I think the pro will be shocked at
> > how strong the program is.”
> >
> > In that case it's time for Lee Sedol to start working hard on turning
> > this match around, because AlphaGo won the second game too! :)
> >
> > Petr Baudis
> > ___
> > 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


-- 
Petr Baudis
If you have good ideas, good data and fast computers,
you can do almost anything. -- Geoffrey Hinton
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go

Re: [Computer-go] AlphaGo won the second game!

[Petri Pitkanen]

This time I think game was tougher. Though too weak to judge. At the end
sacrifice a fistfull stones does puzzle me, but again way too weak to
analyze it.

It seem Lee Sedol is lucky if he wins a game

2016-03-10 12:39 GMT+02:00 Petr Baudis :

> On Wed, Mar 09, 2016 at 09:05:48PM -0800, David Fotland wrote:
> > I predicted Sedol would be shocked.  I'm still routing for Sedol.  From
> Scientific American interview...
> >
> > Schaeffer and Fotland still predict Sedol will win the match. “I think
> the pro will win,” Fotland says, “But I think the pro will be shocked at
> how strong the program is.”
>
> In that case it's time for Lee Sedol to start working hard on turning
> this match around, because AlphaGo won the second game too! :)
>
> Petr Baudis
> ___
> 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] AlphaGo won the second game!

[Petr Baudis]

On Wed, Mar 09, 2016 at 09:05:48PM -0800, David Fotland wrote:
> I predicted Sedol would be shocked.  I'm still routing for Sedol.  From 
> Scientific American interview...
> 
> Schaeffer and Fotland still predict Sedol will win the match. “I think the 
> pro will win,” Fotland says, “But I think the pro will be shocked at how 
> strong the program is.”

In that case it's time for Lee Sedol to start working hard on turning
this match around, because AlphaGo won the second game too! :)

Petr Baudis
___
Computer-go mailing list
Computer-go@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go