Canadian 5th wrote:
The answer lies within the complexity and computing power required to make such an AI. Tic-
tac-toe is so easy a child can solve it, Connect 4 is more difficult but still solvable with highschool level math, Chess is a step above that requiring either a carefully curated move library and carefully programmed tactics or an early model self-learning AI, Go is a step above that requiring a modern cutting edge AI to play well. I would argue that
40k is closer to Chess level and that
MtG is probably slightly above Go level but without any such AI existing I admit that I may well be missing a factor that makes things simpler or more complex for an AI in either of these games.
There are two distinct things
imho : how difficult it is to model a game for a computer to "play" it and evaluate the results of its actions and how long it takes to train said computer. The first thing isn't related to the "complexity" of the game (GO is easy to model, hard to play, which is probably why Deepmind started with Go instead of Starcraft for example) while the second probably is.
But I don't think either of us has the information regarding which game is easier to model and train an AI for, and while it's fun and interesting to talk about, it is complete conjecture for us.
Canadian 5th wrote:Chess is a finite game and thus there should be no uncertainty as to it being solvable, the question is how much computational power (or time) is required to brute force a solution and then how much more power is needed to brute force it within the time allotted for a sanctioned game. In either case, it is a question of hardware and not a logical issue.
Which is what I meant,
afaik we don't know if we will ever reach a state in which we will have enough practical computational power at our disposal (because in theory, such power is limitless, but there are very practical limitations to it) available to "solve" chess.