First, Oliver Zeigermann looks at which algorithms made that success possible and how they are still used within Stockfish, one of the leading chess engines. In this part, he also covers Minimax and AlphaBeta pruning.
However, the emphasis of this machine learning talk is 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, he briefly looks at a great game between Stockfish and AlphaZero and why the era of classic chess engines might be over.
Oliver Zeigermann is a developer and consultant from Hamburg, Germany. He has written several books and has recently published Deep Learning Crash Course with Manning. More on http://zeigermann.eu/
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