topazg wrote:Monte Carlo code is an interesting idea, but IMHO very poor for the future of skilled playing Go engines. I await to see if I'm right or wrong I guess.
In simplest terms, MC bots take a given position, it plays out huge numbers of sequences to the end for a number of moves, and then picks the one that "wins the most times". Over enough iterations, without a great deal of skill or logic in the moves, this works very effectively, but you'll often find an MC bot play a poor endgame, turning a 7.5 point lead into a 1.5 point win - however, get it close to the wire, like 1.5 or 0.5 points, and they play very strongly indeed.
Sure, Monte Carlo bots get defensive and play moves that are suboptimal in terms of points when they are ahead, but why is this considered "unskilled"? Isn't a win by half a point as good as a win by a landslide? In a sense, the computer is just not being greedy by taking more points than it needs to win.
In a position where one player is visibly ahead, there will often be several moves that qualify as perfect play -- that is, the opponent has no sequence of responses that cannot be refuted (in terms of who wins at the end of the game). A sufficiently powerful Monte Carlo bot will choose one of these more or less at random, not caring whether or not it'll win by 7.5 points or 1.5 points at the end of the game. A practical, finite Monte Carlo bot will tend to prefer the more defensive moves, and obviously, it won't always choose perfect play. But your position seems to be one where you could even criticize actual perfect play as "unskilled" or as a "poor endgame", which seems off.
The way I see it, Monte Carlo bots can absolutely become "skilled". They will, however, always play in a style that is not natural to any human, and so their play won't in general resemble that of a skilled human player. The situation we're seeing is one where the strongest computers are not strong because they're imitating strong humans (with opening books etc.), but because they (or their programmers) are actually developing a new style that works very well with the way computers think. That's just the way humans make sense of the game, by thinking of it in terms that work well with the way humans think -- for instance, "good shape" or "influence".
I actually find that an extremely interesting development in the ongoing mind sports human vs. machine rivalry. To the best of my knowledge that's not the way it went with chess?
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