publication . Contribution for newspaper or weekly magazine . 2015

Training Deep Convolutional Neural Networks to Play Go

Clark , Christopher; Storkey, Amos;
Open Access English
  • Published: 01 Jan 2015
  • Country: United Kingdom
Abstract
Mastering the game of Go has remained a longstanding challenge to the field of AI. Modern computer Go systems rely on processing millions of possible future positions to play well,but intuitively a stronger and more ‘human like’ way to play the game would be to rely on pattern recognition abilities rather then brute force computation. Following this sentiment, we train deep convolutional neural networks to play Go by training them to predict the moves made by expert Go players. To solve this problem we introduce a number of novel techniques, including a method of tying weights in the network to ‘hard code’ symmetries that are expect to exist in the target functi...
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Contribution for newspaper or weekly magazine . 2015
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