That doesn't sound different from chess AIs to me. Chess AIs can't "go all the way to the end of the game" until very very late in the game (it's simply impossi

That doesn't sound different from chess AIs to me. Chess AIs can't "go all the way to the end of the game" until very very late in the game (it's simply impossible with current, even projected future, computing power). They too "stop somewhere" to 'evaluate' the board position, and figure out how favorable it is for them: For most chess positions, computers cannot look ahead to all possible final positions. Instead, they must look ahead a few plies and compare the possible positions, known as leaves. The algorithm that evaluates leaves is termed the "evaluation function", and these algorithms are often vastly different between different chess programs. https://en.wikipedia.org/wiki/Computer_chess#Leaf_evaluation https://en.wikipedia.org/wiki/Computer_chess#Leaf_evaluation (It's worth noting that if computers could "go all the way to the end of the game", they could play perfectly, which they can't.) While there are similarities to how professional players play (either game), there are important differences. In particular, professional human players usually look ahead relatively little, but have developed a very accurate intuition for evaluating the board position and for what "feels" like the right next move. This intuition is expected to still be more accurate than the evaluation functions of even the best computer players, which is why anti-computer tactics typically involve "playing conservatively for a long-term advantage": https://en.wikipedia.org/wiki/Anti-computer_tactics https://en.wikipedia.org/wiki/Anti-computer_tactics