Statistical GGP Game Decomposition Aline Hufschmitt, Jean-Noël Vittaut, Nicolas Jouandeau To cite this version: Aline Hufschmitt, Jean-Noël Vittaut, Nicolas Jouandeau. Statistical GGP Game Decomposition. Computer Games - 7th Workshop, CGW 2018, Held in Conjunction with the 27th International Con- ference on Artificial Intelligence, IJCAI 2018, Jul 2018, Stockholm, Sweden. pp.79-97, 10.1007/978- 3-030-24337-1_4. hal-02182443 HAL Id: hal-02182443 https://hal.archives-ouvertes.fr/hal-02182443 Submitted on 15 Oct 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. In Proceedings of the IJCAI-18 Workshop on Computer Games (CGW 2018) Statistical GGP Game Decomposition Aline Hufschmitt, Jean-No¨elVittaut, and Nicolas Jouandeau LIASD - University of Paris 8, France falinehuf,jnv,
[email protected] Abstract. This paper presents a statistical approach for the decompo- sition of games in the General Game Playing framework. General game players can drastically decrease game search cost if they hold a decom- posed version of the game. Previous works on decomposition rely on syn- tactical structures, which can be missing from the game description, or on the disjunctive normal form of the rules, which is very costly to compute.