Vision Transformers for Computer Go
Amani Sagri Tristan Cazenave Jérôme Arjonilla Abdallah Saffidine
Motivated by the success of transformers in various fields, such as language
understanding and image analysis, this investigation explores their application
in the context of the game of Go. In particular, our study focuses on the
analysis of the Transformer in Vision. Through a detailed analysis of numerous
points such as prediction accuracy, win rates, memory, speed, size, or even
learning rate, we have been able to highlight the substantial role that
transformers can play in the game of Go. This study was carried out by
comparing them to the usual Residual Networks.