"Machines reaching a level of play that is consistently better than humans" and "the game is solved" are two completely different statements and it isn't particularly useful to conflate them.
We will likely never be able to solve Go in the formal sense.
Very good point
>We will likely never be able to solve Go in the formal sense.
I'm not sure if it would be precise to say chess will be solved either. The number of outcomes in a 50-move chess game approaches Graham's Number--a number larger than the number of atoms in the observable universe.
In a 100-move game, the number would be many orders of magnitude than an already incomprehensibly large number. So chess also will probably in a precise definition of the word, also never be solved.
Edit: It's kind of mind boggling to think about every atom in the universe representing one position in a game of chess and there not being enough atoms in the universe to represent each one.
10^(number of outcomes in a 50-move chess games) also does not come close.
I did find this interesting statement about Graham's number (unsure of the veracity):
> Graham's number is greater than all of the Planck lengths in the universe. There literally isn't room in the universe to write it out in numerical form.
Edit: It looks like we confused Graham's Number for Shannon's number: https://en.wikipedia.org/wiki/Shannon_number
But according to the Wiki on Shannon's number, a the number of possible outcomes in chess does still far exceed the number of atoms in the universe: >Allis also estimated the game-tree complexity to be at least 10123, "based on an average branching factor of 35 and an average game length of 80". As a comparison, the number of atoms in the observable universe, to which it is often compared, is estimated to be between 4×10^79 and 4×10^81.
I don't believe your comparison between fundamentally different games is sufficient to support your conclusion that an extremely large number of calculations does not pose a challenge for computer programs to solve.
Rather, to the best of my knowledge, to support your conclusion what you would need to do is to prove there exists a method or formula for reducing the number of permutations to a manageable number while still coming to an optimal solution. Apparently if Sudoku is easy to solve, that exists in Sudoku, but it certainly does not yet exist in the realm of human knowledge in chess.
The fact is that Sudoku and many card games are easy to solve, while chess is in fact a much, much more challenging problem for a computer program, and there are a lot of very smart people that have worked on that problem.
HOWEVER, arguing that they aren't solvable purely from a point of view of "the number of possible games / states is greater than the number of particles in the universe" type arguments is that there are many problems we routinely solve with massive search spaces.
Well, you could just do a Google search for yourself to see why your reasoning is wrong. The problem with using a computer to play Go is precisely what I described, the extremely high number of permutations involved, and it's the same concept with chess (Go just has even more of them): https://www.wired.com/2016/01/googles-go-victory-is-just-a-g...
I still disagree with your argument. The problem with Go isn't just the high number of permutations involved, there are real-world problems, with just as many permutations, which have been solved.
The extra problem with Go (and chess to a lesser degree) is that's it's incredibly hard to be sure, with any certainty, to be sure that a move is a "good" choice.
Comparing to the sudoku example again, when "playing" sudoku it's usually obvious as soon as you make a bad move, you've put two '1's in the same row/column/box for example. With Go if we want to play well, or perfectly, we really have to explore the entire search space.
Sudoku is a game, and in which to solve it, a computer program has an obvious method to limit possible permutations to compute in finding a solution. In other words, it is not faced with the challenge of a requirement to compute permutations > 10^86 (roughly atoms in the observable universe).
In contrast to sudoku, chess and go are games which have no yet discovered or theoretical method to limit permutations to solve, therefore to solve them you would be required to computer permutations > 10^86.
So the problem is still with the number of permutations.
Like I said in my other post: if you could develop a technique to reduce the number of permutations while still solving the optimal solution then you would be onto something. Right now no one has been able to dream up such a theory and there are a lot of very smart people who have worked on this problem.
Chess players mentions this a lot. And then they consider chess a sport. For a sport, it shure is a mind boggingly low number of game states :)
(ps: I don't mean to start an uninteresting sport-or-not debate. It is what it is.)
So the fact that Cho Chikun won against a less powerful machine is not necessarily an indication that the entire system is weaker than DeepMind's one. To know that you'd have to run Zen against AlphaGo.
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[1] A big hint of why it didn't is that, at the time, IBM was still selling more hardware than software.
That's an argument against Go having been solved by AlphaGo, not for. If Lee Sedol could beat AlphaGo given the opportunity to practice against it, then nothing is solved.
Also, for a system to dominate against humans in a game it must be able to beat any opponent every time. AlphaGo hasn't demonstrated this yet, so while in the popular opinion AlphaGo "dominates", in the technical sense it does not, and Go won't be "solved" conclusively until it has.
This is false. Ke Jie is far far below Lee Sedol.
Lee Sedol has no equal. Well, AlphaGo beat him but we are talking about player ranks.
With much tighter time constraints, I don't believe machines would do as well because they are using full-breadth search (to my knowledge) -- searching every possibliity. Whereas humans use visual pattern recognition, and we can run this programs quite fast.
Cho Chikun had the large advantage over Lee Sedol that his opponent (Zen) and similar programs (Crazy Stone, Leela) are simply available for him to practice against and probe for weaknesses.
Then of course there's also a significant reduction in the speed of the hardware.
Both of those matter a lot. I won't make a firm statement how relevant the style argument is you mention, but really, don't underestimate those two.