Monte Carlo tree search (MCTS) is a recently proposed search method that combines the
precision of tree search with the generality of random sampling. It has received considerable …

We present a state of the art implementation of the Monte Carlo Tree Search algorithm for
the game of Go. Our Pachi software is currently one of the strongest open source Go …

A multi-armed bandit episode consists of n trials, each allowing selection of one of K arms,
resulting in payoff from a distribution over 0, 1 associated with that arm. We assume …

Fuego is both an open-source software framework and a state-of-the-art program that plays
the game of Go. The framework supports develo** game engines for full-information two …

This thesis studies the use of Monte-Carlo simulations for tree-search problems. The Monte-
Carlo technique we investigate is Monte-Carlo Tree Search (MCTS). It is a best-first search …

Multiplayer Online Battle Arena (MOBA) games have received increasing popularity
recently. In a match of such games, players compete in two teams of five, each controlling an …

In this paper, we examine the use of Monte Carlo tree search (MCTS) for a variant of one of
the most popular and profitable games in the world: the card game Magic: The Gathering (M …

Reinforcement learning and games have a long and mutually beneficial common history.
From one side, games are rich and challenging domains for testing reinforcement learning …

The dominant paradigm for programs playing the game of Go is Monte Carlo tree search.
This algorithm builds a search tree by playing many simulated games (playouts). Each …

Scheduling seeds, ie, selecting seed for mutation from a pool of candidates, significantly
impacts the speed of a greybox fuzzer to achieve a target coverage rate. Despite much …