> How about game with much smaller search tree complexity first, like poker.
I presume you're talking about limit poker. In pot-limit or no-limit poker, the search tree is large, especially (as you say) for 6-max or full-ring. I don't have much of a frame of reference, but I'm tempted to say "very large".
> The problem in poker is not the complexity of the game, it's in learning how your opponent thinks and how they adjust to your play.
I don't understand this distinction. It seems to me that learning how your opponent thinks and how they adjust to your play are a central part of the difficulty in most deep games of strategy.
>It seems to me that learning how your opponent thinks and how they adjust to your play are a central part of the difficulty in most deep games of strategy.
For human players perhaps, but my impression is that most Chess playing software simply tries to find the strongest move, without considering the opponent to any great extent.
The opposite extreme here is Rock Paper Scissors AI, where there is evidently no strongest move, and the only way to do better than a draw is to identify the opponent's strategy.
I think you may be talking past each other. Chess programs, for example, certainly "consider" the opponent. Indeed, they consider the opponent to the extent of mapping out tens of billions of possible opponent moves.
What I believe you're saying is that they don't do is consider the opponent as a unique individual, rather than as a generic opponent to be brute-forced. They don't say, "Oh, well I'm playing against Kasparov, who plays aggressively, so I'll set a trap," versus "I'm playing against Karpov, who overvalues his knights, so I'll threaten them." (Note: these are not actual foibles of Kasparov or Karpov).
Knowing your particular opponent is, it seems to me, a tree-pruning technique, in much the same way that the Monte Carlo approach that is highlighted in the article. If you can anticipate ALL possible opponent responses to an acceptable depth, that's clearly better than making assumptions about how your opponent will respond.
Yeah, they said they didn't understand the distinction, so I was clarifying. Poker leans a lot more towards the Rock Paper Scissors style of AI, where determining the best move becomes much more dependent on understanding your opponent's strategy.
I presume you're talking about limit poker. In pot-limit or no-limit poker, the search tree is large, especially (as you say) for 6-max or full-ring. I don't have much of a frame of reference, but I'm tempted to say "very large".
> The problem in poker is not the complexity of the game, it's in learning how your opponent thinks and how they adjust to your play.
I don't understand this distinction. It seems to me that learning how your opponent thinks and how they adjust to your play are a central part of the difficulty in most deep games of strategy.