Game of Go
This is not about golang, but about the Game of Go.
If you don’t know what it is about, you can discover the game of go on Sensei’s Library - What is Go? and interactively discover the rules of the game by following the tutorial at The Interactive Way to Go (also available in a lot of other languages).
Game resources
- Charles Matthews’ “On Your Side” (fuseki): GoBase - Matthews Fuseki
- Sensei’s Library
- François Mizessyn’s Go Page (french)
- Internet Go School
Computer Go
Go is interesting for a computer scientist because 1) the possible combinations of valid positions outrun by far any computer or computer cluster, forbidding bruteforce approaches and 2) comparative evaluation of two positions is very difficult for a computer.
Traditionally, people tried to make computers play go with algorithms that mimic human reflection and strategy, achieving very poor results (any good beginner could beat the strongest bot). In the past few years, new approaches have come up, like the use of “Monte Carlo” based algorithms (basically bots that play based on the statistics obtained by playing a high number of random games from the actual position, can run massively on parallel independent computers) or CNN (machine learning approach trained on databases of professional games).
- AlphaGo vs Fan Hui: British Go Association - DeepMind 2016 Summary
- AlphaGo vs Lee Sedol: Wikipedia - AlphaGo versus Lee Sedol
- AlphaGo Zero for dummies: Alpha Zero: How and Why it Works