StarCraft II: DeepMind Demonstration: Jan 24 - Page 4

On January 23 2019 11:53 KalWarkov wrote:



until alpha zero beats stockfish in TCEC finals, i will never call alpha zero the strongest engine. everything is controlled by google. no table base, no opening books - which sf isnt trained for.
and still, it isn't live games vs sf11dev.

and who knows if they released all games or are just cherry picking?

On January 23 2019 17:40 Grumbels wrote:
AlphaZero becoming the strongest engine in a matter of hours is a bit deceiving, given that it still required fifty million games of practice and computing a new version of the network every 25k games. It was estimated to take months for the Leela project (open source imitation of AZ), which is distributed on hundreds of computers. Google just has really powerful hardware.

There are some interesting quirks with Leela. For instance, it's not capable of playing endgames efficiently, it seemingly aimlessly moves around, making moves that don't lose the advantage. It doesn't "get to the point". If an SC2 AI is built on the same concept, expect it to not be able to finish off games quickly and take an hour to mine out the entire map and build a fleet of random units to randomly move around the map.
Another quirk of the project is that the algorithm uses not just the current move as input, but also the history of moves. This gives it some measure of what part of the board to pay "attention" to. It also means that if you give it a random position as input, without history, that it can't function. As far as I know Leela is useless in solving tactical puzzles and in handicap games without training it first.
Leela also typically doesn't understand theory of endgames. It doesn't just play them weirdly, but it also doesn't grasp some almost mathematical ideas such as identifying a class of endgames that are drawn despite material imbalances (opposite color bishops, wrong color bishop).
It's apparently also not better at fortress positions, where you have material disadvantages, but your position can't be cracked. There are some known positions like these, and it was hoped that neural networks would be better at them, and would be capable of reasoning that these are a special class of positions that require a different approach. But it doesn't really seem like it.

Leela is also probably already better than Stockfish if you have bad hardware and no opening book. You can imagine that if there was a market for SC2 bots, that they could have opening books updated for every patch and which would have a team of people dedicated to keeping track of the meta and adding knowledge of it to the bot. But Deepmind's AI would use self-learning, i.e. only playing itself and developing its own meta. I don't know if that would make it easier or harder to beat as a human. I think the tree-search method for chess is bound to scale better with hardware than a neural network approach, given that chess is theoretically solvable with tree search. But this method would be useless for SC2, unless the AI uses some sort of abstraction of strategy and tries to think ahead. But I don't think you really need to think ahead in SC2 to get decent results. If you just react to your opponent and have perfect, bot-like control, you will win.

On January 24 2019 03:22 ScarPe wrote:
the problems they had in the beginning was, that it was hard to set up a proper learnming environment. biggest problem was building placement imho.
but remember, once they got the environment the AI will learn by playing 1000 or more games at once. it will overcome human with ease then. even if it learns only very little with every game. the pure mass will do it.

sadly most people think this game would be too hard to learn for an ai, but it will destroy every progamer in the end.