The two require fundamentally different approaches. The difference between those two models is that one focused on imperfect-knowledge games – those where players don’t know the state of all other players, such as their hands in poker – and one focused on perfect-knowledge games like chess, where both players can see the position of all pieces at all times. The other was DeepMind’s AlphaZero, which has beaten the best human players at games like chess and Go. One was DeepStack, the AI created by a team including Schmid at the University of Alberta in Canada and which was the first to beat human professional players at poker.
Martin Schmid, who worked at DeepMind on the AI but who is now at a start-up called EquiLibre Technologies, says that the Student of Games (SoG) model can trace its lineage back to two projects. The AI, called Student of Games, was created by Google DeepMind, which says it is a step towards an artificial general intelligence capable of carrying out any task with superhuman performance. A single artificial intelligence can beat human players in chess, Go, poker and other games that require a variety of strategies to win.
