When did Monte Carlo tree search emerge as a concept?
The Monte Carlo method emerged in the 1940s as a way to solve deterministic problems using random sampling. Researchers began applying these ideas to game playing software by the late 1980s.
Questions about Monte Carlo tree search
Short answers, pulled from the story.
Who coined the term Monte Carlo tree search and when was it introduced?
Rémi Coulom coined the term Monte Carlo tree search in 2006 while applying the Monte Carlo method to game-tree search. That same year Levente Kocsis and Csaba Szepesvári developed the Upper Confidence bounds applied to Trees algorithm known as UCT.
What happened when AlphaGo played Lee Sedol in March 2016?
In March 2016 AlphaGo defeated Lee Sedol four games to one earning an honorary 9-dan title. The system used Monte Carlo tree search together with artificial neural networks for both policy and value estimation.
How does Monte Carlo tree search differ from alpha-beta pruning?
Monte Carlo tree search offers advantages over alpha-beta pruning especially in games with high branching factors. It does not require an explicit evaluation function since implementing game mechanics alone suffices to explore the search space.
When did Google Deepmind release AlphaGo?
Google Deepmind released AlphaGo in October 2015 becoming the first computer program to beat a professional human Go player without handicaps on a standard 19x19 board.