Optimizing UCT for settlers of catan

Gabriel De Arruda Rubin De Lima, Bruno Fortes Paz, Felipe Rech Meneguzzi

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2017 Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2017
PublisherIEEE Computer Society
Pages164-172
Number of pages9
ISBN (Electronic)9781538648469
DOIs
Publication statusPublished - 28 Jun 2018
Event16th Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2017 - Curitiba, Brazil
Duration: 2 Nov 20174 Nov 2017

Conference

Conference16th Brazilian Symposium on Computer Games and Digital Entertainment, SBGames 2017
Country/TerritoryBrazil
CityCuritiba
Period2/11/174/11/17

Keywords

  • Artificial Intelligence
  • Monte Carlo Tree Search
  • Settlers of Catan

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