but, of course, you are right. I simply have
not studied their deep reading carefully enough to witness more incidents.
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On 30.10.2017 19:22, Pierce T. Wetter III wrote:
this car and this child
In Germany, an ethics commission has written ethical guidelines for
self-driving cars with also the rule to always prefer avoiding
casualties of human beings.
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earning rules, practising
problems etc. Conscious, explicit thinking can be trained by learning
rules, practising problems etc. So what do you want to say?
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ain their decision-making have said that they could
not because it would be intuition. A framework that is NOT theory.
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tc. to code - yes.
If you can build Go bot about KGS 3/4dan strength
Using my approach, I expect several manyears, which I do not have for
that purpose.
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Accepted, thank you!
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be applied.
What you describe has been used with success and better success than I
expect what my knowledge-pure approach can currently achieve. But MCTS
as glue for conflicting principles has also run into a boundary. I want
to see that boundary surpassed by my pure approach.
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On 24.10.2017 20:19, Xavier Combelle wrote:
totally unrelated
No, because a) software must also be evaluated and can by go theory and
b) software can be built on exact go theory. That currently (b) is
unpopular does not mean unrelated.
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e for related proofs) or will be published by me later (will be
quite a lot and have practical relevance, but you need to be patient).
Research in mathematical go theory requires much time because exactness
is often necessary and proving can be tricky
discussions resulting to something.
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me consequences they
can have. Rarities are one very good study tool for this purpose.
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as terminal positions with disturbing life kos or anti-sekis,
whether ladders are recognised beyond 250 moves etc. Not to mention
non-go applications.
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from Deepmind for the published AlphaGo Zero games.
Are they for free use or copyrighted? I hope the former so everybody
including Deepmind can see more commentaries.
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ready been described but if not this would be an interesting research
topic.
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increasingly important in view of the
fast progress of AI. Surely you are aware that Deepmind knows this.
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it to be financially worthwhile for the "too specialised"
case of Go? As I say, a mathematical proof of a complete solution of Go
will occur before AI playing perfectly;)
So far neural
nets have been trained and applied within single domains, and any
"generalization" means with
On 20.10.2017 09:38, Xavier Combelle wrote:
What is currently named nanorobot is simply hand assembled molecules
which have mechanical properties and need huge
framework to be able simply move.
Sure. But we must not wait until such a thing exists.
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r plants, to start with.
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-replicate or permanently ensure energy access,
from causing extinction of mankind?
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if not $25. At least, I
hope.
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iterate komi increments for specific positions during the games and
create a second instance of AlphaGo modified due to its improved play
with tougher komi.
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ccess to physical
ressources), they can render extinct mankind.
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On 09.08.2017 20:50, John Tromp wrote:
The number of games is at most 361^#positions.
This misses passes, rules distinguishing situations etc. and infinite
sequences under some rulesets.
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this
successfully.)
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's moves - only by AlphaGo's "reading" depth.
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On 31.01.2017 16:39, Gian-Carlo Pascutto wrote:
http://senseis.xmp.net/?BasicLivingEyeShapes
Warning: these do not include any living eye shapes with inside stones,
nor specialities on the edge or in the corner.
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"such that", "would", "eye", "proper",
"involves".)
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I suppose we still send messages to computer-go@computer-go.org
Yes, if I receive this message from the list.
I suppose nothing has changed about the procedures and email addresses
for (un)subscription.
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inking, 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.
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to)
Reasoned decision-making need not always be low-level / mathematical.
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ing 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.
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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.
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matical proofs ALA the NN does not emulate mathematical proving.
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unt 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.
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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
Intelligence and it is
used for a task involving responsibility, such as health care or car
driving. Who has which legal responsibility if the General Artificial
Intelligence makes mistakes killing people?
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, old variations) you find in Joseki 3 - Dictionary.
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ad proverbs are about learning josekis without understanding:
learn, forget, repeat; this effort can demote a player's strength indeed;)
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ducational
tool! It would probably even help teach joseki.
No. Joseki learning requires much more than move suggestions.
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cateful study of the few moves after the
squeeze is necessary.
You mention several outdated principles and concepts, whose
insufficiency I have explained elsewhere.
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ly if it were proven
mathematically.
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On 26.03.2016 06:15, Robert Jasiek wrote:
9d does not exist.
I mean as a real world rank. Of course, there are servers in which ranks
are derived from ratings. E.g., KGS 9d can mean everything from real
world 3d [sic!] to 9p.
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5d - 6d.
9p has a great range in itself.
Rating systems can have a problem of running away ratings at the top.
Self-played ratings might not be significant.
5 games are not enough to assign a secure rank to AlphaGo v. 18.
So, no, the graph is not nice.
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For those of you not reading forums but interested in a positional
judgement after the tower squeeze sacrifice in game 5, an SGF is
attached inline. Conclusion: afterwards White has at least a small lead,
so AlphaGo's strategy was superb.
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(;SZ[19]GM[1]CA[UTF-8]FF[4]ST[2
was a
little better at that moment.)
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,
and groups of pupils.]
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On 14.03.2016 09:33, Petri Pitkanen wrote:
And being 600 elo points above best human you are pretty close to best
possible play.
You do not have any evidence for such a limit.
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preceding sequence
is a well-timed, cute trick play and the Alphago teams needs to
understand why the trick worked. I'd guess that it would have found a
correct reply if the moyo defense had been a local, short term problem.
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Such should prevent the program from suddenly experiencing harshly
dropping probabilities during a few successive moves / mistakes of the
game, such as in game 4 of the AlphaGo - Lee Sedol match.
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not artificially restrict strategy a lot.
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know if this is advantageous considering
presumably greater GPU time)
- instead of single position patterns, use combinations of current
position and later positions, for different (dynamic) parameters of time
shift, so as to model long-term effects
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right side in sente) and creating a winning position by robbing White of
every option of creating significant new territory regions / expansions.
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theory and the generated dynamic data
(structures)
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nt advantage of the
program's revealed strategic mistakes to demonstrate AlphaGo's limits.
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different
degrees of safety of (potential) territory and the strategic concepts of
sacrifice and exchange.
I have also suggested other definitions, but IMO they are less
attractive for NN.
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Aja, sorry to bother you with trivialities, but how does Alphago avoid
power or network failures and such incidents?
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onnection trouble, server bugs of
distributed computers, hardware bugs of the local interface computers or
interrupted power supply.)
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be the optimum but a smaller percentage
must be the best.
(Roughly) which percentage is optimal? Why? Is the optimum greater or
smaller than 57%?
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cl. myself).
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On 04.02.2016 02:52, David Ongaro wrote:
At the same time I've to point out that you seem to plan to get very old.
I will not see the solution, which needs at least another 400 years
unless computers learn to research.
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f semantic conflicts.
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ecause too many have lost themselves
in the black hole of ambiguous string theory. Computer go theory seems
to be similar to physics.
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amateur
comments were related to reading or by heart knowledge of the latest
nadare variations (before the post-joseki aji mistakes, which can be
detected by 5d, or even below), but reading / joseki is not AlphaGo's
weakness.
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is a heuristic / engineering / first guess" are easily
possible. Research papers should be honest. (They may hide secret
details, but this is another topic.)
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trict "definition" of nakade? Has
anybody proceeded beyond my definition attempts? I suspect the standard
problem of research again: definition by reference to a different paper
with an ambiguous description. If ambiguous terms are presumed for
pragmatic reasons, this must be stated!
On 02.02.2016 13:05, "Ingo Althöfer" wrote:
For research in general it is good to have waves:
Research is faster if informalism and formalism progress simultaneously
(by different people or in different papers).
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, provided it is clearly stated that it is an ambiguous heuristic
and not an [unambiguous] definition / term. References / links (possibly
iterative) hiding ambiguity without declaring it are inappropriate.
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ons for undefined terms, principles, methods etc. Human beings
can better learn if they know what to learn because the contents is
described clearly.
about what is rapidly
approaching as human cognition automateable.
Eh? Besides GoTools, there has been very little, AFAIK.
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re I would want to confirm Myongwan
Kim's related opinion.
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nce as go players, yes. But... I have seen too many
surprising sequences and sacrifices to be sure.
Then we estimate the decision complexity to be upper bounded by
200^181 and the game tree complexity by 200^361.
I won't believe such until proven:)
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lligence solved" - never heard greater nonsense before.
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be considered
and the upper bound is ca. N^P.
For the yellow press: "The number of 10^80 atoms in the universe is much
smaller than the number 2 * 10^170 of possible positions, which is very
much smaller than the uncountable number of possible different games."
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ralised game on boards with N
intersections (but go as a game is played on the 19x19 board with its
fixed N = 361).
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players' positional evaluation
exists, see e.g. my two books Positional Judgement.
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ambiguous, the most often correct /
applicable) descriptions of human-understandable go theory and further
research in the latter.
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afu.de/jasiek/c2002.pdf
http://home.snafu.de/jasiek/c2002com.pdf
with the flawless Area Scoring in general.
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of computational complexity?
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things as "attack a group for the same of
making an additional 1 point in sente during this particular sequence".
With histograms, you see nothing like this in the near future, I'd guess.
Define 'fight'! (As you understand it for your study purpose.)
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seki much different from ordinary life and
death? Why care if anything is a seki? Maybe it is sufficient to study
histograms of final global scores and detect at which tree branches
peaks arise. (Or do likewise for subpositions.)
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arch and Wolf would have suitable programs to use but I have - for
me - more urgent tasks, such as continuing research on ordinary semeais.
Would strong go bots also fall in this category?
I do not know because I have seen too few games played by
KGS) seeks seki as a reasonable compromise in
unreasonable fights.
***
If you want to study seki configurations, the best is to do theoretical
research. If you want many ordinary sekis in actual games, take KGS samples.
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Is playing bad moves good for aesthetics? No? Then why call it
aesthetics? Call it perfect / good play. The most "beautiful" stone is
bad if it is dead.
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values if the task is to assess current positions rather than final
scoring positions, in which one value is sufficient.
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-alive from either player's perspective, allowing UNDEFINED where
necessary. For the sake of simplicity, n, m > 2 or < -2 you can replace
by 2 or -2.
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On 06.11.2015 10:47, Aja Huang wrote:
area scoring, in which case the score is almost always odd.
Black wins: odd score
White wins: even score
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more.
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as expert system knowledge.
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short overview
http://home.snafu.de/jasiek/RobertJasiekGoTheoryResearch.html
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.)
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to be coded and maybe of the complexity of time remain.
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; quiescience has been familiar to CG for a
long time.)
I wish you the best of luck producing the set of principles.
Luck is useless. What has helped me was careful analytical study of my
own (often methodical) thinking.
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ups strength was the core concept feeding into the full board evaluation,
which tried to estimate the score.
But what WAS your group strength...?:)
Score estimation of a given position should also depend on territory
counts, not only on group strength etc.
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to 100, 10, 10 for the sake of expert system input,
but even then the implementation task is huge (man-years). Not to
mention semantic testing of processed data to get a "thinking" workload
similar to my own thinking.
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that needs some "calculation" and basic
counting or limited reading fail, MC can come in to do the calculation.
E.g., an expert system can identify groups of likely connected strings,
then MC can calculate if indeed (statistically) the connection is given.
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and
connection status, for what purposes did you use them and how did you
apply them?
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How much computation time do you expect to reveil the complete exact
19x19 number? Or is more research necessary before I may ask this?
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presuppositions) or is research in understanding it not advanced far enough?
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as ordinary
MC because some expert knowledge is necessary or must be approximated
heuristically. Needless to say, keep the computational complexity of
this expert knowledge low.
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, but then we will not understand much in terms of go
theory why the programs will excel. For getting much understanding of go
theory from programs, human/program collaboration will be necessary anyway.
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