How do Chess Engines work? Looking at Stockfish and AlphaZero | Oliver Zeigermann

  Рет қаралды 65,548

MLCon | Machine Learning Conference

MLCon | Machine Learning Conference

4 жыл бұрын

Speaker: Oliver Zeigermann (embarc) | mlconference.ai/speaker/olive...
Game playing is a classic discipline of AI and had a major break through in the 90s when Deep Blue defeated Kasparov and arguably became the world’s best chess player. First, we will look which algorithms made that success possible and how they are still used within Stockfish, one of the leading chess engines. Here, we will cover Minimax and AlphaBeta pruning.
However, the emphasis of this talk will be on Monte Carlo Tree Search and its advanced use in AlphaZero that relies on zero human heuristics and without even an opening library. You will learn how it trains using self play on a convolutional ResNet architecture. At the end, we will briefly look at a great game between Stockfish and AlphaZero and why the era of classic chess engines might be over.
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Пікірлер: 65
@YourMakingMeNervous
@YourMakingMeNervous 3 жыл бұрын
This is still by far the best lecture I've seen on the topic so far
@Frost_Byte_Tech
@Frost_Byte_Tech 2 жыл бұрын
It's because of content like this that I'll never get bored of trying to solve complex problems, really insightful and thought provoking 💫
@LouigiVerona
@LouigiVerona 3 жыл бұрын
An incredible lecture, thank you!
@mohamedyasser2068
@mohamedyasser2068 Жыл бұрын
attending such a lecture for me is a dream , I can't believe that most of them don't play chess !!
@A_Swarm_of_Waspcrabs
@A_Swarm_of_Waspcrabs 4 жыл бұрын
Great lecture- that hour whizzed by too fast.
@philj9594
@philj9594 Жыл бұрын
Just started learning chess and I know only a little about computer science/programming but this was wonderful to gain a better understanding of what chess engines are actually doing under the hood when I use them and also a better understanding of their limitations. I've noticed many people talk about people over-relying on engines so I figured it would be a good use of my time to gain a deeper understanding of what a chess engine even is if I'm going to be using them regularly. Also, it's just interesting and fun to learn! Thanks for the amazing lecture. :)
@allorgansnobody
@allorgansnobody Жыл бұрын
Wow just 4 minutes in and this is an excellent explanation. Just knowing whether or not stockfish had these "handcrafted" elements is so important to understanding how it works.
@kevingallegos9466
@kevingallegos9466 Жыл бұрын
Please what is the song at the beginning of the video! I've heard it before and now I want to listen to it! Thankyou!
@christrifinopoulos8639
@christrifinopoulos8639 Жыл бұрын
about the stockfish evaluation function, is it completely prewritten or are there some (handwritten) parameters that can be optimised through learning? (
@sunnysunnybay
@sunnysunnybay Жыл бұрын
Without analysing as a chess engine i can see it's actually better for black. Count 9 pieces around the king, both queens are at the 5th rank of the king so they are not included, but black has a rook while no rook is near the white king and the pawn structure has 1 shape out for them too, agains't 3 move on black and good defense around them with both pawn and major pieces. Black has 1 pawn on the 5th rank in font of this weak king also, while it's 1 pawn for H rank & G & E for white.
@berndmayer3984
@berndmayer3984
the best investigation yielded approx. 10^42 positions and that is what counts.not the rough estimate of 10^120 possible games.
@ruffianeo3418
@ruffianeo3418 Жыл бұрын
There is one point, usually never mentioned. I will try to explain that (rather valid question) below, hoping, someone else will explain, why this is not a concern:
@vladimirtchuiev2218
@vladimirtchuiev2218 2 жыл бұрын
I don't understand why do you need the value function, if you have probabilities over possible moves, you will always during deployment select the argmax of the probability vectors... Is it for victory/defeat flags or something like that? Also, after each iteration of the MCTS, is the network trained until convergence or do you go over the self-played game only once?
@peterwinters8587
@peterwinters8587 4 жыл бұрын
Monte Carlo probability has been around decades
@desertplayz3955
@desertplayz3955 Жыл бұрын
I wanna see stockfish pull a Jerome opening now
@ME0WMERE
@ME0WMERE 2 жыл бұрын
10:45
@GNU_Linux_for_good
@GNU_Linux_for_good 3 жыл бұрын
sacrifice the rook [Rc1+] in order to prevent an immediate mate.
@danruth1089
@danruth1089
tHANK YOU, but I disagree that rook usage
@avlavas
@avlavas 2 жыл бұрын
Intel Core i7 11700K
@Best-go8cd
@Best-go8cd 4 жыл бұрын
u need a degree in computer science to know how AlphaZero work
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