[Computer-go] Are the AlphaGols coming?
"Ingo Althöfer"
one thousand years ago, the was a cry of terror:
The Mongols are coming!
Now it seems we have entered a new age:
The AlphaGols are coming!
Not only from Britain, not only from Google, not only from Japan (Zen).
But also from China!
Look here (thx to German Bonobo for making it public in the
German computer Go forum!):
http://www.lifein19x19.com/forum/viewtopic.php?f=10&t=13913
******************************************
What will we see in 2017?
Will top humans get handicap stones from the AlphaGols?
Puzzled, Ingo.
_______________________________________________
Computer-go mailing list
Compu...@computer-go.org
http://computer-go.org/mailman/listinfo/computer-go
"Ingo Althöfer"
Tobias Pfeiffer
This reddit is later on linked in the forum and includes speculations
that it's not AlphaGo based on answers in similar positions. I'd
disagree though - no whole game is the same and AlphaGo evolves and
changes so much still through self-play.
https://www.reddit.com/r/baduk/comments/5l3l7e/chinese_ai_crushing_pros_on_fox_server/
"Ingo Althöfer"
here is a link to the German Computer Go forum:
http://www.dgob.de/yabbse/index.php?topic=6381.msg208264#msg208264
The grey box shows the list of 30 games played by
the "Master bot. All these games were won by the bot!
Paweł Morawiecki
Hi,
The grey box shows the list of 30 games played by
the "Master bot. All these games were won by the bot!
Game 31: black2012 = Li Qincheng
Game 32: 星宿老仙 = Gu Li
Game 33: 星宿老仙 = Gu Li
Game 34: 我想静静了 = Dang Yifei
Game 35: 若水云寒 = Jiang Weijie
Game 36: 印城之霸 = Gu Zihao
Game 37: pyh = Park Yeonghun
Game 38: 天选 = Tuo Jiaxi
"Ingo Althöfer"
> There have been another 8 games on Foxwq server:
> ...
> Totally, 38-0. It looks like a kind, indirect (yet powerful), message
> from DeepMind to Chinese Go Association: "Please, let us try a real
> challenge, like 3-handicap games, it does not really make much sense
> to play even anymore".
So, do you want to say that "Master" might be AlphaGo?
From the disucssion I thought that "Master" was a chinese bot.
If Aja is reading: can you enlighten us?
Cheers, Ingo.
Lukas van de Wiel
From the thread we already read Aja's enlightenment:
/u/emdio pointed out:
From a previous time in which a bot was suspicious to be AlphaGo:
"I can confirm it's not AlphaGo or a weaker version of AlphaGo. We
haven't decided to play AlphaGo online yet, but when the decision is
made we will use AlphaGo(P) on tygem and AlphaGoBot on KGS.
Aja"
Cheers and happy new year!
Lukas
Paweł Morawiecki
So, do you want to say that "Master" might be AlphaGo?
From the disucssion I thought that "Master" was a chinese bot.
"Ingo Althöfer"
a good collection of arguments and thoughts, thank you.
> I'd put all my money it's AlphaGo...
How much money do you have?
You may answer in private mail, if appropriate.
Ingo.
PS. I have designed a LEGO scene on Frisbee Go:
http://www.dgob.de/yabbse/index.php?action=dlattach;topic=6385.0;attach=5581;image
Yamato
On 2017/01/02 21:47, Lukas van de Wiel wrote:
> From the thread we already read Aja's enlightenment:
>
> /u/emdio pointed out:
> From a previous time in which a bot was suspicious to be AlphaGo:
> "I can confirm it's not AlphaGo or a weaker version of AlphaGo. We
> haven't decided to play AlphaGo online yet, but when the decision is
> made we will use AlphaGo(P) on tygem and AlphaGoBot on KGS.
> Aja"
This comment was about GoBeta last April.
If "Master" (or something) is AlphaGo, he should have a strong reason
not to use the name AlphaGo. So probably Aja cannot answer this, because
he does not lie.
By the way, I found this tweet interesting :)
https://twitter.com/ScienceNews/status/814559161312808965
Yamato
"Ingo Althöfer"
> ... This comment was about GoBeta last April.
>
> If "Master" (or something) is AlphaGo, he should have a strong reason
> not to use the name AlphaGo. So probably Aja cannot answer this, because
> he does not lie.
>
> By the way, I found this tweet interesting :)
> https://twitter.com/ScienceNews/status/814559161312808965
thanks for the explanation and your "interesting"-sniplet.
By the way: A bet on Master's identity is underway.
The idea is that the bet is undecided, if the question is not resolved
until the start of the European Go Congress (July 22 - August 06, 2017)
in Oberhof (Thuringia; near Jena).
The computer go day in the EGC will very likely be Wednesday, August 02.
Ingo.
Janzert
> Hello Paweł,
>
>> There have been another 8 games on Foxwq server:
>> ...
>> Totally, 38-0. It looks like a kind, indirect (yet powerful), message
>> from DeepMind to Chinese Go Association: "Please, let us try a real
>> challenge, like 3-handicap games, it does not really make much sense
>> to play even anymore".
>
> So, do you want to say that "Master" might be AlphaGo?
> From the disucssion I thought that "Master" was a chinese bot.
>
> If Aja is reading: can you enlighten us?
>
> Cheers, Ingo.
Looks like we have an official answer in the affirmative
https://twitter.com/demishassabis/status/816660463282954240
Jim O'Flaherty
"Ingo Althöfer"
what shall I say.
> Gesendet: Mittwoch, 04. Januar 2017 um 16:11 Uhr
> Von: Janzert <jan...@janzert.com>
> ...
> On 1/2/2017 7:05 AM, "Ingo Althöfer" wrote:
> > Hello Paweł, ...
> Looks like we have an official answer in the affirmative
> https://twitter.com/demishassabis/status/816660463282954240
This means that I lost my bet with Paweł.
He will get a nice meal in a nice restaurant from me
(probably during the European Go Congress 2017 in Oberhof).
Ingo.
David Ongaro
Richard Lorentz
Thank you very much!
-Richard
"Ingo Althöfer"
> ... can somebody please update me (us?) a
> the opponents?
they were all strong pro players. Ke Jie (humanity's last hope
in the eyes of several go players) also played three of the
games.
Thinking times were small base times plus 3 byoyomi periods of
30 seconds each.
****************************************************
I remember the nice A Capella Song on Alpha Go from
March 2016 (only the first 30 seconds are relevant):
https://www.youtube.com/watch?v=dh_mfGo183Y
From the text:
>> AlphaGo! AlphaGo! ...
>> Ruler of the board ...
>> We welcome our silicon overlord.
Originally it was "overlords", but at the moment we have only one.
Ingo.
Adrian Petrescu
Thomas Rohde
On 2017-01-04 at 21:41, Richard Lorentz <richard...@csun.edu> wrote:
> Having fallen a bit out of the loop can somebody please update me (us?) a little on these 60 games. How strong were the opponents? Are some/most/all actually pros? What was the time control? What is the Foxwq server?
Many 9d pros, among them Ke Jie, Park Junghwan, Gu Li … see the SGF archive that Marcel Grünauer compiled: http://rechne.net/dl/the_master_files.zip
60 won games in a row :-o
Greetings, Tom
--
Thomas Rohde
Wiesenkamp 12, 29646 Bispingen, GERMANY
------------------------------
+49 5194 6741 | t...@bonobo.com
Horace Ho
Robert Jasiek
>humanity's last hope
The "last hope" are theoreticians creating arcane positions far outside
the NN of AlphaGo so that its deep reading would be insufficient
compensation! Another chance is long-term, subtle creation and use of aji.
--
robert jasiek
Xavier Combelle
Le 05/01/2017 à 07:37, Robert Jasiek a écrit :
> On 04.01.2017 22:08, "Ingo Althöfer" wrote:
>> humanity's last hope
>
> The "last hope" are theoreticians creating arcane positions far
> outside the NN of AlphaGo so that its deep reading would be
> insufficient compensation! Another chance is long-term, subtle
> creation and use of aji.
>
The problem is that you have to find a way to constraint alphago to
reach the position you have prepared it will be very hard because it has
the choice of half of the moves which leads to the position.
From computer science point of view, theoricaly, the best move on an
arbitrary position being a PSPACE hard problem, any problem at least
easier than PSPACE could translate in a go problem. So there is a huge
amount of difficult problems (understand impossible to solve except on
toy size) which could be setup as target go positions but the real
problems is that you have to reach this position which are very unlikely
to happen in a real game.
An easy way to win against Alphago strength level of bot is to make two
deterministic version of it, make it play one against the other and
replay the moves of the wining side.
--
Xavier
Paweł Morawiecki
[...]So my question is: is it possible to have reverse Komi games by feeding the value network with reverse colors?
Also having 2 stone games is not so interesting since it would reveal less insights for even game opening Theory.
Detlef Schmicker
what makes you think the opening theory with reverse komi would be the
same as with standard komi?
I would be afraid to invest an enormous amount of time just to learn,
that you have to open differently in reverse komi games :)
Detlef
Am 05.01.2017 um 10:50 schrieb Paweł Morawiecki:
> 2017-01-04 21:07 GMT+01:00 David Ongaro <david....@hamburg.de>:
>
>>
>> [...]So my question is: is it possible to have reverse Komi games
>> by feeding the value network with reverse colors?
>>
>
> In the paper from Nature (subsection "Features for policy/value
> network"), authors state:
>
> *the stone colour at each intersection was represented as either
> player or opponent rather than black or white. *
>
> Then, I think the AlphaGo algorithm would be fine with a reverse
> komi. Namely, a human player takes black and has 7.5 komi. The next
> step is that AlphaGo gives 2 stones of handicap but keeps 7.5 komi
> (normally you have 0.5).
>
> Aja, can you confirm this?
>
>
>> Also having 2 stone games is not so interesting since it would
>> reveal less insights for even game opening Theory.
>>
>
> I agree with David here, most insights we would get from even
> games. But we can imagine the following show. Some games are played
> with a reverse komi, some games would be played with 2 stones (yet,
> white keeps 7.5 komi) and eventually the main event with normal
> even games to debunk our myths on the game. Wouldn't be super
> exciting!?
>
> Best regards, Paweł
>
>
>
Paweł Morawiecki
what makes you think the opening theory with reverse komi would be the
same as with standard komi?
Thomas Rohde
On 2017-01-05 at 04:07, Horace Ho <hor...@gmail.com> wrote:
> The players and the results (in Chinese):
>
> [..]
passing this on :-)
Greetings, Tom
Jim O'Flaherty
Robert Jasiek
> For each arcane position reached, there would now be ample data for AlphaGo
> to train on that particular pathway.
No. (E.g., which data for four octuple kos?)
Jim O'Flaherty
David Ongaro
> On Jan 5, 2017, at 2:37 AM, Detlef Schmicker <d...@physik.de> wrote:
>
> Hi,
>
> what makes you think the opening theory with reverse komi would be the
> same as with standard komi?
>
> I would be afraid to invest an enormous amount of time just to learn,
> that you have to open differently in reverse komi games :)
Thats why I used the comparative adjective “less”. It might not be ideal, but still much better than changing the fundamental structure of the opening with an extra stone. Furthermore the effect might not as big as you think:
1. The stronger player doesn’t have to play overplays when the handicap is correct. If the handicap is correct and if AlphaGo “knows” that is another question though… Of course the weaker player might play differently (i.e. more safely) but at least that is something he or she can control
2. One could even argue the other way around: we might see more sound (theoretically correct) moves from AlphaGo with reverse Komi. If it's seeing itself ahead already during the opening it might resort to slack but safe moves. Since it’s still winning we can be left wondering if it was actually a good move. But if it does an unusual looking move which it can’t be considered an overplay but it’s still winning in the end with reverse Komi there should be a real insight to gain.
Still, a reverse Komi handicap is rather big, but it might be the next best thing we have without retraining the value network from scratch. Furthermore retraining the value network will probably affect the playing style even more.
Thanks,
David O.
David Ongaro
Jim O'Flaherty
Robert Jasiek
> Two amateur players where analyzing a Game and a professional player happened to come by.
> So they asked him how he would assess the position. After a quick look he said “White is
> leading by two points”. The two players where wondering: “You can
count that quickly?”
Usually, accurate positional judgement (not only territory but all
aspects) takes between a few seconds and 3 minutes, depending on the
position and provided one is familiar with the theory.
--
robert jasiek
Robert Jasiek
> I don't follow.
1) "For each arcane position reached, there would now be ample data for
AlphaGo to train on that particular pathway." is false. See below.
2) "two strategies. The first would be to avoid the state in the first
place." Does AlphaGo have any strategy ever? If it does, does it have
strategies of avoiding certain types of positions?
3) "the second would be to optimize play in that particular state." If
you mean optimise play = maximise winning probability.
But... optimising this is hard when (under positional superko) optimal
play can be ca. 13,500,000 moves long and the tree to that is huge. Even
TPU sampling can be lost then.
Afterwards, there is still only one position from which to train. For NN
learning, one position is not enough and cannot replace analysis by
mathematical proofs ALA the NN does not emulate mathematical proving.
terry mcintyre
Sent from Yahoo Mail for iPad
Jim O'Flaherty
Robert Jasiek
> into a position with superko [...] how do you even get AlphaGo into a the arcane
> state in the first place,
I can't in practice.
I have not provided a way to beat AlphaGo from the game start at the
empty board.
All I have shown is that there are positions beyond AlphaGo's
capabilities to refute your claim that AlphaGo would handle all
positions well.
Hui and Lee constructed positions with such aspects: Hui with long-term
aji, Lee with complex reduction aji. Some versions of AlphaGo mishandled
the situations locally or locally + globally.
> The professional players will be
> open to all sorts of creative ideas on how to find weaknesses with AlphaGo.
Or the amateur players or theoreticians.
> Perhaps you can persuade one of the 9p-s to explore your idea
> of pushing the AlphaGo AI in this direction.
Rather I'd need playing time against AlphaGo.
> IOW, we are now well outside of provable spaces
For certain given positions, proofs of difficulty exist. Since Go is a
complete-information game, there can never be a proof that AlphaGo could
never do it. There can only ever be proofs of difficulty.
> mathematical proof around a full game
From the empty board? Of course not (today).
> We cannot formally prove much simpler models,
Formal proofs for certain types of positions (such as with round_up(n/2)
n-tuple kos) exist.
Jim O'Flaherty
Robert Jasiek
> I hope you get access to AlphaGo ASAP.
More realistically, I (we) would need to translate the maths into
algorithmic strategy then executed by a program module representing the
human opponent. Such is necessary because no human can remember
everything to create a legal superko sequence of over 13,500,000 moves
or have the mere stamina to perform it. (Already just counting to 1
million is said to take 3 weeks without sleep...)
Anyway,...
> exploring AI weaknesses
...this is a major objective. E.g., we do not want AI driven cars
working right most of the time but sometimes killing people because the
AI faces situations (such as a local sand storm or a painting on the
street with a fake landscape or fake human being) outside its current
training and reading.
Xavier Combelle
> ...this is a major objective. E.g., we do not want AI driven cars
> working right most of the time but sometimes killing people because
> the AI faces situations (such as a local sand storm or a painting on
> the street with a fake landscape or fake human being) outside its
> current training and reading.
it is very more likely to happen than an AI killing me because a mistake
in programming (I know, it is not the point of view of most of people
which want a perfect AI with zero dead and not an AI which would reduce
the death on road by a factor 100)
David Doshay
Nick Wedd
Gonçalo Mendes Ferreira
or AI driven cars, but if it were the same I'd prefer to have drunk
drivers. Drunk drivers you can understand: you can improve your chances
by making yourself more visible, do not jump from beyond obstacles, be
more careful when crossing or not crossing before they actually stop. A
failure in an AI car seems much more unpredictable.
Gonçalo
Xavier Combelle
Xavier Combelle
to dead by an AI driven than a human driven as the expectation set to
AI driven is at least one order of magnitude higher than human one
before there is any hope that AI would be authorized (Actually the real
expectation is AI would be responsible of zero death)
Álvaro Begué
David Ongaro
On 06.01.2017 03:36, David Ongaro wrote:Two amateur players where analyzing a Game and a professional player happened to come by.> leading by two points”. The two players where wondering: “You can count that quickly?”
So they asked him how he would assess the position. After a quick look he said “White is
Usually, accurate positional judgement (not only territory but all aspects) takes between a few seconds and 3 minutes, depending on the position and provided one is familiar with the theory.
Jim O'Flaherty
Robert Jasiek
>> accurate positional judgement
> you also rely on “feelings” otherwise you wouldn’t be able to survive.
In my go decision-making, feelings / subconscious thinking (other than
usage of prior sample knowledge, such as status knowledge for particular
shapes) have an only marginal impact. For me, they serve as a
preselection filter besides my used methodical preselection filters. In
blitz, the impact is larger when time is insufficient for always using
the methodical ones.
Another factor is my pruning of reading. I would not describe it as
"feelings / subconscious thinking" but as "prune according to knowledge
/ principles AFA time allows, otherwise call my mental random generator
for deciding what else to prune". I.e., it is a conscious calling of
random for particular purposes.
Instead of suspecting feelings, read my books
- Positional Judgement 1 - Territory
- Positional Judgement 2 - Dynamics
to better understand why my accurate positional judgement does not need
feelings / subconscious thinking. Even in ca. 1/3 of my blitz (10' SD)
games, I can apply it (less frequently per game, OC).
About the only relevant feeling permitted in my go is a contribution to
the decision on my first move as Black, which may also depend on my mood
(besides opponent, komi, time, knowledge).
18+ years ago, I used feelings and the like for quite a few decisions
during the middle game and (early) endgame. Decision by feelings led to
low winning probability so I decided to overcome them by creating much
more profound theory, which improved my play and enabled(!) me to
survive (to use your words) as a go teacher and go book author.
> Mathematically (the approach you seem yourself constrain into)
Reasoned decision-making need not always be low-level / mathematical.
David Ongaro
> On Jan 9, 2017, at 6:51 AM, Robert Jasiek <jas...@snafu.de> wrote:
>
> On 09.01.2017 07:19, David Ongaro wrote:
> >> accurate positional judgement
>> you also rely on “feelings” otherwise you wouldn’t be able to survive.
>
> In my go decision-making, feelings / subconscious thinking (other than usage of prior sample knowledge, such as status knowledge for particular shapes) have an only marginal impact. For me, they serve as a preselection filter besides my used methodical preselection filters. In blitz, the impact is larger when time is insufficient for always using the methodical ones.
It is understandable that you believe that. That seems to be one of these strong illusions wich are helping survival. But tests have shown that decisions are normally made subconsciously seconds before we get aware of them (and therefore seconds before we consciously rationalize them). Among others John-Dylan Haynes did a lot of interesting related experiments for that. E.g see a short summary for two of them at https://www.youtube.com/watch?v=CT43MogXAjI&feature=youtu.be&t=8m3s. Don’t be distracted by the fact that these where relatively simple experiments, with not much reasoning for making a choice involved. E.g. split brain experiments have shown that people can rationalize their action with one half of their brain while the other half actually did the decision and action for a different reason. The scary part is that they are convinced that the rationalization was actually the reason for their action. (If needed I can look up references for this, but I guess you already heard about these experiments.)
I’m sure if you could make such a test while playing a Go game you would be surprised about the results.
David O.
PS: It should be said that “feeling” was an inaccurate word here, but I gather from your answer that you understood what I meant: i.e. the unconscious decision process. In fact, when we get aware of a “feeling”, when defined in the stricter sense as a product by the "limbic system”, the decision may already have been made.
Robert Jasiek
> decisions are normally made subconsciously seconds before we get
> aware of them
Essentially nothing is known how to interpret such neurological
findings. It is (usually) not like the universe was forcing me
unexpected subconscious thinking into my conscious mind. My
topic-dependent thinking occurs because I want to be busy thinking about
the topic for a long time (such as successive minutes or hours - not
seconds as in the tests - during a go game). In such a thinking context,
both subconscious and conscious thinking related to the topic occur with
countless interactions in both directions (and even occasional level
changes of subconscious pieces accessible as conscious, but this is not
so interesting, it is like reading in assembler;) ) Now, if some test
claims to observe that subconscious thinking preceded conscious
thinking, this is like making assumptions of excluding parts of
conscious thinking. As if you wanted to deceive Heisenberg's uncertainty
relation. Maybe it does play a relevant role in brains. Observation
affects perception.
--
robert jasiek