Re: [Computer-go] Are the AlphaGols coming?

[Robert Jasiek]

On 09.01.2017 23:03, David Ongaro wrote:
> 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
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Re: [Computer-go] Are the AlphaGols coming?

[David Ongaro]

> On Jan 9, 2017, at 6:51 AM, Robert Jasiek  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=youtu.be=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.
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Re: [Computer-go] Are the AlphaGols coming?

[Robert Jasiek]

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.


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.

--
robert jasiek
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Re: [Computer-go] Are the AlphaGols coming?

[Jim O'Flaherty]

David, that's a fantastic and succinct summarization. Tysvm!


On Jan 9, 2017 12:19 AM, "David Ongaro"  wrote:

> On Jan 5, 2017, at 10:49 PM, Robert Jasiek  wrote:
>
>
> On 06.01.2017 03:36, David Ongaro wrote:
>
> 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.
>
>
> Believe it or not, you also rely on “feelings” otherwise you wouldn’t be
> able to survive.
>
> Some see DNNs as some kind of “cache” which has knowledge of the world in
> compressed form. Because it's compressed it can’t always reproduce learned
> facts with absolute accuracy but on the other hand it has the much more
> desired feature to even yield reasonable results for states it never saw
> before.
>
> Mathematically (the approach you seem yourself constrain into) there
> doesn’t seem to be a good reason why this should work. But if you take the
> physical structure of the world into account things change. In fact there
> is a recent pretty interesting paper (not only for you, but surely also for
> other readers in this list) about this topic: https://arxiv.org/abs/
> 1608.08225.
>
> I interpret the paper like this: the number of states we have to be
> prepared for with our neural networks (either electronic or biological) may
> be huge, but compared to all mathematically possible states it's almost
> nothing. That is due to the fact that our observable universe is an
> emergent result of relatively simple physical laws. That is also the reason
> why deep networks (i.e. with many layers) work so well, even though
> mathematically a one layer network is enough. If the emergent behaviours of
> our universe can be understand in layers of abstractions, we can scale our
> network linearly by the number of layers matching the number of
> abstractions. That’s a huge win over the exponential growth required when
> we need a mathematical correct solution for all possible states.
>
> The “physical laws” for Go are also relatively simple and the complexity
> of Go is an emergent result of these. That is also the reason why the DNNs
> are trained with real Go positions not just with random positions, which
> make up the majority of all possible Go positions. Does that mean the DNNs
> won’t perform well when evaluating random positions, or even just the
> "arcane positions” you discussed with Jim? Absolutely! But it doesn’t have
> to. That’s not its flaw but its genius.
>
> David O.
>
>
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