[angelofm]

I played poker part time heads up (one against one) previously and the amount of study and analyses players have to do is huge to only get to a reasonable level.

This challenge is very unfair to players so I wouldn't say it won, players have a massive disadvantage, every professional player has tracking software and a database to analyse every decisions that has been made.

This is of course extremely important because you can model your strategy to exploit the suboptimal decisions made by your opponent, yet players have no access to any of these tools, so the bot adjusts it's play based on their human opponents but humans cannot do the same and are left with a guessing game.

If they want to make a proper challenge then players need to have access to the tools they usually use playing in the Internet.

[Anderkent]

>o the bot adjusts it's play based on their human opponents but humans cannot do the same and are left with a guessing game

Do we know if it actually does it? I imagine it's much simpler to build a bot that plays a balanced profitable strategy rather than one that tries to build a model of their opponent and exploit it.

[deong]

It's stated in the article. During a day's play, the AI suggests plays based on its current knowledge. At night, the day's events are fed into the system for it to learn on for the next day.

I assume there are probably papers that specify what form of learning is taking place, but the article didn't go into that level of detail and I haven't tried to track it down.