Bayesian Optimization in AlphaGo

arXiv: Learning, Volume abs/1812.06855, 2018.

Cited by: 43|Views182
EI

Abstract:

During the development of AlphaGo, its many hyper-parameters were tuned with Bayesian optimization multiple times. This automatic tuning process resulted in substantial improvements in playing strength. For example, prior to the match with Lee Sedol, we tuned the latest AlphaGo agent and this improved its win-rate from 50% to 66.5% in sel...More

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