49

No, it can't. Even if you had it train on a zillion self-playing games and it miraculously achieved perfect play somehow, we would have no way of proving that it had achieved perfect play without first solving chess some other way and then comparing AlphaZero's play to perfect play in all possible positions. Its approach simply doesn't result in a solution ...


27

It sort of did. "Sort of" because once you examine how neural networks work it's not clear what AlphaZero is actually learning. AlphaZero has a neural network evaluation function. How that works is that it takes as input the position on the board (along with other things like whether a pawn can capture en passant, whether castling is possible, etc) ...


15

The short answer is: No. AlphaZero learns to evaluate only the position. The position consists of all the pieces and their placement on the board (plus castling and en-passant information). There is no way to distinguish the material's value from the position's strength -- which is a really beautiful idea and offers a lot of learning potential for humans. ...


8

Nope. AlphaZero's entire architecture (and the architectures of most other engines) is such that it cannot "find a solution", and in any case, if a solution was to be found it would be through programs meant to do just that. Such programs do not exist, due to the absurd complexity. Also, note that AlphaZero (as far as I know) is no longer under ...


8

One central piece of alphazero is the neural evaluation function. This function takes the board as input and produces a value as output. The only input is what pieces are on the board and where. So, you can see it as the programmers enforcing this rule: the value of a position depends on which pieces are placed where. This is what the AI "knew" as ...


6

From the comments below, maybe a good summary of this answer: Alphazero doesn't necessarily respect piece value the way we do, but both Alphazero's experience and our piece valuation (which is effectively our human experience) are approximations of same the balance of power for a given board state. Piece value is a form of bias, by inherent definition of ...


6

No, it is impossible, even for Alpha Zero. Solving chess in a scientific sense means to prove the value of every possible move in every possible position. Without a mathematic model still to be found, that means: brute force calculation from the regular starting position (or even all 960 starting positions of Chess960) to a regular end: mate, stalemate, dead ...


5

Compressibility When we talk about chess, we almost always talk about time, because for humans, that is the relevant variable. But when you talk about the space of all games, time suddenly shrinks into the background, and you suddenly realize: "this is an enormous space". When we talk about "proofs", we think of things which are a few ...


5

AI engineer here. The answer to this question is hiding in the name: AlphaZero. This refers to "zero prior knowledge of the game". AlphaZero can also play Go. Now, it might be a bit strong to say that AlphaZero has absolutely no knowledge about chess. AlphaZero knows that it's a turn-by-turn board game, and that the 3 possible outcomes are a win ...


3

In short, no there was no explicit concept of relative piece importance coded in. But the weights that the neural network ends up learning probably indirectly account for piece values. That said, this AlphaZero paper claims that AlphaZero's neural network output best fits these piece values:


1

This is a short answer, but hopefully it helps. Consider how AlphaZero values pawns. It throws them away in disgust sometimes, usually to open up files or diagonals on which to plant menacing rooks and bishops. AlphaZero doesn't care one bit about the nominal value a piece may have (I'd argue most human players also don't care about a piece's value).


1

I don't know how to play Go at all, but the paper wrote: History features Xt, Yt are necessary, because Go is not fully observable solely from the current stones, as repetitions are forbidden For chess, I'm unable find any mention about it in the paper other than: Unless otherwise specified, the training and search algorithm and parameters are identical ...


1

We can start by asking what it means to "solve" a problem. It seems to me that this is almost an unanswerable question. It means in practice that a sufficient number of "experts" are convinced by the "proof" We have this situation in Mathematics, with the famous Haken-Appel computer proof of the four-color theorem, where a ...


1

Stockfish stopped using opening books a long time ago. That is, it's an engine, and if you want to use an opening book, you have to use it in UI that you use to play the game or in the software you use to interface with the engine, playing book moves without even telling Stockfish about that. There's no way to tell Stockfish about existing books (the ...


1

Here, it is crucial that AlphaZero is based on a Deep Neural Network (DNN) which essentially means that the network consists of many layers of, mostly, different types (regarding how the information is collected and processed). This allows such networks to subdivide the evaluation problem to a large (and flexible) number of elements it can process separately ...


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