Monte-Carlo Tree Search for the “Mr Jack” Board Game

Abstract : Recently the use of the Monte-Carlo Tree Search algorithm, and in particular its most famous implementation, the Upper Confidence Tree can be seen has a key moment for artificial intelligence in games. This family of algorithms provides huge improvements in numerous games, such as Go, Havannah, Hex or Amazon. In this paper we study the use of this algorithm on the game of Mr Jack and in particular how to deal with a specific decision-making process. Mr Jack is a 2-player game, from the family of board games. We will present the difficulties of designing an artificial intelligence for this kind of games, and we show that Monte-Carlo Tree Search is robust enough to be competitive in this game with a smart approach
Type de document :
Article dans une revue
International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) , 2015
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01406506
Contributeur : Fabien Teytaud <>
Soumis le : jeudi 1 décembre 2016 - 11:40:43
Dernière modification le : mardi 12 décembre 2017 - 15:32:01
Document(s) archivé(s) le : lundi 20 mars 2017 - 17:25:03

Fichier

MrJack.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01406506, version 1

Collections

Citation

Ahmad Mazyad, Fabien Teytaud, Cyril Fonlupt. Monte-Carlo Tree Search for the “Mr Jack” Board Game. International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) , 2015. 〈hal-01406506〉

Partager

Métriques

Consultations de la notice

73

Téléchargements de fichiers

49