Monte-Carlo tree search is a powerful paradigm for the game of Go. We present a parallel Master-Slave algorithm for Monte-Carlo tree search. We experimented the algorithm on a netw...
Monte-Carlo evaluation consists in estimating a position by averaging the outcome of several random continuations, and can serve as an evaluation function at the leaves of a min-ma...
Recently, Monte-Carlo Tree Search (MCTS) has become a popular approach for intelligent play in games. Amongst others, it is successfully used in most state-of-the-art Go programs....
Guillaume Chaslot, Mark H. M. Winands, Istvan Szit...
Abstract. Games are considered important benchmark tasks of artificial intelligence research. Modern strategic board games can typically be played by three or more people, which m...
We apply Monte Carlo simulation and alpha-beta search to the card game of Skat, which is similar to Bridge, but different enough to require some new algorithmic ideas besides the t...