Settlers of Catan is one of the main representatives of modern strategic board games and there are few autonomous agents available to play it due to its challenging features such as stochasticity, imperfect information, and 4-player structure. In this paper, we extend previous work on UCT search to develop an automated player for Settlers of Catan. Specifically, we develop a move pruning heuristic for this game and introduce the ability to trade with the other players using the UCT algorithm. We empirically compare our new player with a baseline agent for Settlers of Catan as well as the state of the art and show that our algorithm generates superior strategies while taking fewer samples of the game.
|Title of host publication||Proceedings - 2017 Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2017|
|Publisher||IEEE Computer Society|
|Number of pages||9|
|Publication status||Published - 28 Jun 2018|
|Event||16th Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2017 - Curitiba, Brazil|
Duration: 2 Nov 2017 → 4 Nov 2017
|Conference||16th Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2017|
|Period||2/11/17 → 4/11/17|
Bibliographical notePublisher Copyright:
© 2017 IEEE.
- Artificial Intelligence
- Monte Carlo Tree Search
- Settlers of Catan