Artificial Intelligence - Special issue on computer chess
Games, computers and artificial intelligence
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
World-championship-caliber Scrabble
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Games solved: now and in the future
Artificial Intelligence - Chips challenging champions: games, computers and Artificial Intelligence
Real-time decision making for adversarial environments using a plan-based heuristic
Real-time decision making for adversarial environments using a plan-based heuristic
Bandit based monte-carlo planning
ECML'06 Proceedings of the 17th European conference on Machine Learning
Node-expansion operators for the UCT algorithm
CG'10 Proceedings of the 7th international conference on Computers and games
Design with shape grammars and reinforcement learning
Advanced Engineering Informatics
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Games are considered important benchmark opportunities for artificial intelligence research. Modern strategic board games can typically be played by three or more people, which makes them suitable test beds for investigating multi-player strategic decision making. Monte-Carlo Tree Search (MCTS) is a recently published family of algorithms that achieved successful results with classical, two-player, perfect-information games such as Go. In this paper we apply MCTS to the multi-player, non-deterministic board game Settlers of Catan. We implemented an agent that is able to play against computer-controlled and human players. We show that MCTS can be adapted successfully to multi-agent environments, and present two approaches of providing the agent with a limited amount of domain knowledge. Our results show that the agent has a considerable playing strength when compared to game implementation with existing heuristics. So, we may conclude that MCTS is a suitable tool for achieving a strong Settlers of Catan player.