That chess is less robotic, is perhaps not obvious. A postmodern skepticism of “even in principle” thinking is part of it: who cares what’s possible in principle, when in practice that is inaccessible to me? The actual narrative is me versus this player, my blunders versus her blunders, and whoever blunders less wins. There is a Platonic Form of perfect play that has no blunders? It is discovered by computers? See, this is something I had to acclimate to in learning chess, because chess engines are available, they will rank your games and tell you that this opening is slightly better than that opening by a tenth of a pawn, and you have to like just throw them in the trash. It's like a standard of beauty that demands you have half a percent body fat and rippling abs and bench 300 easy. And instead you have the desire to be Interesting, rather than to be True.
I play some openings because they are silly, you chase my knight in a massive circle around the board and then I am totally undeveloped but you are questionably developed and it is not clear you are doing better. Gone are the days of memorized 20-deep trees of Sicilian openings where I got a careful half-pawn advantage in my theory and then turned out to blunder my queen and erase it all. That was, if you like, a half-life.
By contrast, say, backgammon gives you a transferable skill of luck-creation and the strength of being vulnerable and well, I don't know what exactly cube management is but something to the effect of the wisdom about when to cut out early versus when to stick with something to the bitter end. They are different skills.
Baseball teaches a transferable skill of perseverance, of "hey you are going to miss most of the pitches and in fact if you consistently hit a 25% batting average you can easily ride that into a professional career."
Trying to evaluate any of these in terms of its impact on "real life decision-making" is probably doomed to failure, no?
Here is a good post on bots, if you haven't seen it: https://int8.io/counterfactual-regret-minimization-for-poker...
Over the last 15 years or so high level poker strategy has increasingly focused on approximating GTO play, and people are moving away from any type of exploitative play, whether that's psychological tells or adjusting to weaknesses like an opponent folding too much. So a GTO player actually will bluff quite frequently, but it's due to the math indicating that it's an advantageous spot to do it, not because of anything he's observed about his opponent.
That said, there's still room to adjust to exploit an opponent, and the weaker the opponent is the more profitable it can be to deviate from "correct" play.
I wonder about this distinction. This seems it would make sense if all the players played the GTO strategy. Suppose one agent were to play the GTO strategy, but an other player was vulnerable to bluffing. It seems reasonable to "tune" the bluffs to that player.
In an extreme example, suppose every time a certain player would fold 100% of the time when another player played a certain way. It seems it would make sense for that other player to play that way when they wanted that player to fold, even under normal circumstances that play would be suboptimal.
This article explains it better than I could:
http://blog.gtorangebuilder.com/2014/03/gto-poker-outside-of...
(cue the often useless, recursive aspects of pop-culture game theory)
Clarification: If you played with cards face up no one would ever make a mistake. You could calculate the odds and the math would be perfect. The goal of poker is to make an opponent make a mathematically incorrect play.
A simple example is a rock paper scissors tournament. The nash equilibrium says you must always simply pick each with 1/3 chance. But if you play this you are almost gauranteed to finish in the middle of the pack. The winner is going to be someone who can take advantage of other players. There used to be a rps AI tournament years ago (UofAlberta I think), and this is why they wouldn’t take submissions that only played nash equilibrium play.
But you are right, in that usually the first step in getting good at poker is to simply play the strength of your cards based on your position. And this becomes more amd more important the higher the stakes since players tend to be better there.
It's also true against someone who is playing an exploitative strategy.
Even on-line heads-up challenges are played on 2 tables in order to not be boring and that is 500-600+ hands per hour
The most interesting part now is the meta. Once you know someone well it's easier to find their tells. Unless they know that and adjust. The final 4 at the table is really fun every week.
Unfortunately, in terms of winning strategies, this couldn't be further from how the game actually plays out today. Back when online poker exploded onto the scene, the old cash game pros quickly discovered that their way of playing the game (described in books like super system and theory of poker) was obsolete.
Seeing veteran poker pros getting crushed in their home turf by teenagers whose playing style was forged in the crucible of online multitabling was the ultimate expose to that old mystique of poker as a psychological battle of deception. One could say that the internet players through their mechanistic play were approximating strategies that were at their core, algorithmic. It's not at all surprising then, to see poker bots today utterly crush certain variants of the game. It won't be long, before poker as a whole succumbs.