Python Reinforcement Learning Projects

Go and other board games

Researchers have already created AI programs that outperform the best human players in board games such as chess and backgammon. In 1992, researchers from IBM developed TD-Gammon, which used classic reinforcement learning algorithms and an artificial neural network to play backgammon at the level of a top player. In 1997, Deep Blue, a chess-playing program developed by IBM and Carnegie Mellon University, defeated then world champion Garry Kasparov in a six-game face off. This was the first time that a computer program defeated the world champion in chess.

Developing Go playing agents is not a new topic, and hence one may wonder what took so long for researchers to replicate such successes in Go. The answer is simple—Go, ...