Deep Learning and the Game of Go by Max Pumperla & Kevin Ferguson

Author:Max Pumperla & Kevin Ferguson [Pumperla, Max & Ferguson, Kevin]
Language: eng
Format: epub, mobi
Publisher: Manning Publications Co.
Published: 2022-03-27T22:00:00+00:00

You might ask yourself how strong a bot you can potentially build with the methods presented in this chapter. A theoretical upper bound is this: the network can never get better at playing Go than the data you feed it. In particular, using just supervised deep-learning techniques, as you did in the last three chapters, won’t surpass human game play. In practice, with enough compute power and time, it’s definitely possible to reach results up to about 2 dan level.

To reach super-human performance of game play, you need to work with reinforcement-learning techniques, introduced in chapters 9 to 12. Afterward, you can combine tree search from chapter 4, reinforcement learning, and supervised deep learning to build even stronger bots in chapters 13 and 14.

But before you go deeper into the methodology of building stronger bots, in the next chapter we’ll show you how to deploy a bot and let it interact with its environment by playing against either human opponents or other bots.

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