A New Way To Search Game Trees.

The article focuses on the use of variations of Monte Carlo tree search (MCTS) that may allow artificial intelligences (AI) to prevail against human opponents in the game Go. It states MCTS uses random sampling in decision making to quickly distinguish strong and weak moves in Go. It talks about the use of game-tree search that allows AIs to prevail in the games checkers and chess, but which is less viable in Go. It suggests that algorithms used in game playing have applications in other fields.