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.