ml-alphago-2016-deep-nn-tree-search

IN premise — entries/2026/06/21/wiki-Machine_learning-chunk-7.md

Created 2026-06-21T09:55:51+00:00

AlphaGo (Silver et al., 2016) demonstrated deep neural networks combined with tree search mastering the game of Go

Dependents

These beliefs depend on this one:

• IN game-playing-validates-neural-search-hybrid — Game-playing demonstrates that neural networks achieve superhuman performance through two distinct paradigms — AlphaGo (2016) combined deep neural networks with tree search to master Go, while a transformer achieved grandmaster-level chess (Elo 2895) using pure static evaluation without any search — suggesting that both hybrid (neural+search) and pure neural approaches can reach expert-level game play, with each paradigm's dominance depending on the game's computational structure.