In this article we present an overview on the state of the art in games solved in the domain of
two-person zero-sum games with perfect information. The results are summarized and some …

" The Encyclopedia of Library and Information Science provides an outstanding resource in
33 published volumes with 2 helpful indexes. This thorough reference set--written by 1300 …

Fuelled by successes in Computer Go, Monte Carlo tree search (MCTS) has achieved wide-
spread adoption within the games community. Its links to traditional reinforcement learning …

Monte-Carlo search has been successful in many non-deterministic games, and recently in
deterministic games with high branching factor. One of the drawbacks of the current …

Monte Carlo search, and specifically the UCT (Upper Confidence Bounds applied to Trees)
algorithm, has contributed to a significant improvement in the game of Go and has received …

Humans and machines are very different in their approaches to game playing. Humans use
intuition, perception mechanisms, selective search, creativity, abstraction, heuristic abilities …

Search algorithms are often categorized by their node expansion strategy. One option is the
depth-first strategy, a simple backtracking strategy that traverses the search space in the …

So far the game of Domineering has mainly been investigated by combinatorial-games
researchers. Yet, it is a genuine two-player zero-sum game with perfect information, of which …

Recently, the list of solved two-person zero-sum games with perfect information has
increased. The state of current knowledge is that many games are a win for the first player …

Abstract Monte Carlo Tree Search (MCTS) is an effective decision making algorithm that
often works well without domain knowledge, finding an increasing application in commercial …