I wouldn’t say that poker is “much easier than the classic deterministic games”, and poker AI still lags significantly behind humans in several regards. Basically, the strongest poker bots at the moment are designed around solving for Nash equilibrium strategies (of an abstracted version of the game) in advance, but this fails in a couple of ways:
These approaches haven’t really been extended past 2- or 3-player games.
Playing a NE strategy makes sense if your opponent is doing the same, but your opponent almost always won’t be. Thus, in order to play better, poker bots should be able to exploit weak opponents. Both of these are rather nontrivial problems.
Kriegspiel, a partially observable version of chess, is another example where the best humans are still better than the best AIs, although I’ll grant that the gap isn’t a particularly big one, and likely mostly has to do with it not being a significant research focus.
I wouldn’t say that poker is “much easier than the classic deterministic games”, and poker AI still lags significantly behind humans in several regards. Basically, the strongest poker bots at the moment are designed around solving for Nash equilibrium strategies (of an abstracted version of the game) in advance, but this fails in a couple of ways:
These approaches haven’t really been extended past 2- or 3-player games.
Playing a NE strategy makes sense if your opponent is doing the same, but your opponent almost always won’t be. Thus, in order to play better, poker bots should be able to exploit weak opponents.
Both of these are rather nontrivial problems.
Kriegspiel, a partially observable version of chess, is another example where the best humans are still better than the best AIs, although I’ll grant that the gap isn’t a particularly big one, and likely mostly has to do with it not being a significant research focus.