Collaborating Authors


Monte Carlo Tree Search: Implementing Reinforcement Learning in Real-Time Game Player


In this article, to answer these questions, we go through the Monte Carlo Tree Search fundamentals. Since in the next articles, we will implement this algorithm on "HEX" board game, I try to explain the concepts through examples in this board game environment. If you're more interested in the code, find it in this link. There is also a more optimized version which is applicable on linux due to utilizing cython and you can find it in here. Monte Carlo method was coined by Stanislaw Ulam for the first time after applying statistical approach "The Monte Carlo method".

University of Alberta Computer Hex Research Group

AITopics Original Links

Welcome to the home page of the computer Hex research group. We --- Kenny Young, Kelly Li, Broderick, Phil, Ryan, Jakub (and previously Aja, David, Jack, Mike, Morgan, Nathan Po, Maryia, Martha, Leah, Yngvi, Geoff Ryan, and Robert Budac) --- build Hex players and solvers. The group informally dates from 1999, when Jack, who wrote Queenbee, started an MSc with Jonathan. Current projects include MoHex, and Solver. Previous projects include Wolve, Mongoose and Queenbee.

Game of Hex -- from Wolfram MathWorld

AITopics Original Links

Hex is a two-player game invented by Piet Hein in 1942 while a student at Niels Bohr's Institute for Theoretical Physics, and subsequently and independently by John Nash in 1948 while a mathematics graduate student at Princeton. The game was originally called Nash or John, with the latter name at the same time crediting its inventor and referring to the fact that it was frequently played on the tiled floors of bathrooms (Gardner 1959, pp. The name Hex was invented in 1952, when a commercial version was issued by the game company Parker Brothers. Hex is played on a diamond-shaped board made up of hexagons. The game is usually played on a boards of size 11 on a side, for a total of 121 hexagons, as illustrated above.