[yAnonymous]

Links were posted here: https://news.ycombinator.com/item?id=13535714

As expected, the AI is good at making technically correct decisions and "draining money" from a table by playing hands with sufficient data almost perfectly.

However, in decisive all-in situations with little information available, it supposedly wouldn't do so well, regardless of all the learning, but that's what it often comes down to.

>Nash Equilibrium is a strategy which ensures that the player who is using it will, at the very least, not fare worse than a player using any other strategy.

How do you make this work for situations that can cost you the game in one hand, with little information available? Without observing the opponent's behavior you can't, and for the AI that means it can be forced into making bad calls by playing aggressively, unless the game mode allows for avoiding such decisions, which was the case in this test.