This approach also works for Hanabi, which is a very interesting game. You can't see your own cards, but the other players can. I bought the game because someone on a reinforcement learning podcast [2] mentioned it, and actually played it multiple times.
This puts the earlier "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning", 2022 [1] in some perspective. Apparently the "mastering" in 2022 wasn't quite there yet. Four years later, the new approach seems to actually be better than humans.
This approach also works for Hanabi, which is a very interesting game. You can't see your own cards, but the other players can. I bought the game because someone on a reinforcement learning podcast [2] mentioned it, and actually played it multiple times.
[1] https://en.wikipedia.org/wiki/Hanabi_(card_game)
[2] https://www.talkrl.com/episodes/jakob-foerster
I recall playing this game as a preschooler. It was mostly psychology and bluff. Very interesting.
This puts the earlier "Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning", 2022 [1] in some perspective. Apparently the "mastering" in 2022 wasn't quite there yet. Four years later, the new approach seems to actually be better than humans.
[1] https://arxiv.org/abs/2206.15378
Wait, wasn't there that strong stratego bot that came out from deepmind in 2022?
The article talks about that. The new bot required two orders of magnitude less training data and plays better.
Awesome, I will read this carefully later today. I'm always excited by AI research applied to games.
So cute, like some news story from 2019.