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Edit: You don't have to go far to see that DeepMind are pushing AlphaZero as "general purpose". This is the title of their Science paper on it:

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

http://science.sciencemag.org/content/362/6419/1140

"General" as in what? As opposed to reinforcement learning, in er, general? As opposed to other ANN architectures?

>> I am in no way dismissing AlphaZero's truy remarkable abilities in both chess and other games like go and shogi.

More to the point- it's only chess, go and shogi; not games "like" those.

The AlphaZero architecture has the structure of a chessboard and the range of moves of pieces in chess, go and shogi hard-coded and you can't just take a trained AlphaZero model and apply it to a game that doesn't have either the board or the moves of those three games.

To be blunt, AlphaZero has mastered chess, go and shogi, but it can't play noughts-and-crosses.



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