towforce wrote: Laskos wrote: Laskos wrote:
My experience of playing human chess masters is that I think I'm doing better than I expected, then suddenly a win for the opponent emerges.
If Crazy Stone genuinely had a good evaluation, it would be able to beat human opponents. Maybe it is weak at evaluating the "frameworks" that will eventually become territory?
It might also be related to some deeper tactics too, from what I saw, these "weak" (much stronger than me anyway) engines lose large fights too to strong humans, so it's not clear to me whether the general assessment of the position is to blame for their weakness.
AlphaGo lost to tesuji, so it seems I was about right. The evaluation can hardly help in unique long line fights, MCTS seems to be to blame. Let's see in the 5th game if it is a systematic weakness.
I have been thinking further about game four, and I have 2 further ideas I'd like to hear some feedback on, please:
1. AlphaGo's intelligence isn't very "generalised" - so when positions arise that don't suit its expertise, it under performs compared to a human of similar strength
I wouldn't say that. AlphaGo would play well in most, even weird, but quiet positions. It will approximate them just fine to a pattern. But this backfires when approximations don't work. In sequences of unique moves it suffers. In fact I would be curious to see how would AlphaGo perform on Go problems compared to reasonably strong humans (not even top professionals). In both games 4 and 5 AlphaGo miscalculated 10-12 "plies" races to capture, sequences of unique moves. In these races, pattern matching and approximations are not very useful, one has to have a better search. It was interesting to see that in the points where AlhpaGo stumbled, Crazy Stone (MCTS too) stumbles badly too. In game 5, AlphaGo miscalculated a race to capture in lower right part, a thing even strong amateur players wouldn't do. Crazy Stone does the same, here is its evaluation of the whole game:
White and Black moves 24-28, where a sequence of unique tactical moves is required, are completely misevaluated. Crazy Stone thinks that White gained a large advantage, while it's an important tactical loss for White, almost game-changing. Also, observe from the graphic that Crazy Stone completely misses to notice all the fights which occurred later, and which were potentially game-changing too. AlphaGo is much better, but I bet it failed to see too the often game-changing nature of local fights, races to capture, invasions. And it's probably due to the inadequacy of the MCTS.
2. the team have focused on getting an advantage and holding it. What they weren't aware of is that in honing that skill, they were making it very poor in losing positions. In winning positions, their program plays very well - but in losing positions, they should switch to an entirely different strategy (almost a completely different program) whose aim is nothing less than to create absolute bloody mayhem!
I think this is easily corrected. It's probably not hard to make AlphaGo a bit weaker but more human in its goal: to capture as much territory as it can instead of purely maximizing its probability of win. Also when losing, it could go to some swindle mode and fool around by fighting for every local point, invading and such. That's double. I am not sure how the point 1) will be solved.