Classic approaches to game AI require either a high quality of domain knowledge, or a long
time to generate effective AI behaviour. These two characteristics hamper the goal of …

Monte-Carlo Tree Search (MCTS) is a new best-first search guided by the results of Monte-
Carlo simulations. In this article, we introduce two progressive strategies for MCTS, called …

Abstract Monte-Carlo Tree Search (MCTS) is a new best-first search method that started a
revolution in the field of Computer Go. Parallelizing MCTS is an important way to increase …

Classical methods such as A* and IDA* are a popular and successful choice for one-player
games. However, they fail without an accurate admissible evaluation function. In this paper …

Games are considered important benchmark opportunities for artificial intelligence research.
Modern strategic board games can typically be played by three or more people, which …

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 …

Classic methods such as A∗ and IDA∗ are a popular and successful choice for one-player
games. However, without an accurate admissible evaluation function, they fail. In this article …

Current search engines such as Google and Yahoo! are prevalent for searching the Web.
Search on dynamic client-side Web pages is, however, either inexistent or far from perfect …

The design of interplanetary trajectories often involves a preliminary search for options later
refined/assembled into one final trajectory. It is this broad search that, often being …

Determinization is a technique for making decisions in games with stochasticity and/or
imperfect information by sampling instances of the equivalent deterministic game of perfect …