Using search algorithm statistics for assessing maze and puzzle difficulty

A video game’s difficulty has a large impact on player engagement. For instance, it is crucial in some genres to give the players a challenge difficult enough without frustrating them. We propose a simple method for assessing game-level difficulty as a precursor to adapting it to a specific player....

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Detalles Bibliográficos
Autores: Valenzuela Muñoz, Elio Matías, Schaa, Hans, Barriga, Nicolas A., Patow, Gustavo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10256/27306
Acceso en línea:http://hdl.handle.net/10256/27306
Access Level:acceso abierto
Palabra clave:Algorismes computacionals
Computer algorithms
Videojocs
Video games
Simulació per ordinador
Computer simulation
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spelling Using search algorithm statistics for assessing maze and puzzle difficultyValenzuela Muñoz, Elio MatíasSchaa, HansBarriga, Nicolas A.Patow, GustavoAlgorismes computacionalsComputer algorithmsVideojocsVideo gamesSimulació per ordinadorComputer simulationA video game’s difficulty has a large impact on player engagement. For instance, it is crucial in some genres to give the players a challenge difficult enough without frustrating them. We propose a simple method for assessing game-level difficulty as a precursor to adapting it to a specific player. In particular, we propose using simple performance metrics of algorithms such as A* and Breadth-First Search (BFS) as a proxy for the difficulty of puzzles. We performed user studies using a 2D maze simulator and a Sokoban game implementation; both built into the Unity game engine. We show that, for 2D mazes generated by Binary Space Partitioning, the number of nodes expanded by BFS highly correlates with the number of steps a human player takes to reach the goal. For Sokoban puzzles, the closed list length of an A* search is highly correlated to perceived difficulty and the number of movements a human player takes to solve the puzzle. These results show that simple metrics are probably good enough to assess a given level’s difficulty, which is a first step towards being able to personalize the difficulty of a maze or a puzzle to a particular playerThis research was partially funded by the National Agency for Research and Development (Agencia Nacional de Investigación y Desarrollo, ANID Chile), ANID-Subdirección del Capital Humano/Doctorado Nacional/2023-21230824 and FONDECYT Iniciación grant 11220438. This work was also partially funded by project PID2021-122136OB-C22 from Ministerio de Ciencia e Innovación, Spain. Open Access funding provided thanks to the CRUE-CSIC agreement with ElsevierElsevierAgencia Estatal de Investigación2025info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionpeer-reviewedapplication/pdfhttp://hdl.handle.net/10256/27306http://hdl.handle.net/10256/27306Entertainment Computing, 2025, vol. 53, art. núm. 100925Articles publicats (D-IMA)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)Inglésinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.entcom.2025.100925info:eu-repo/semantics/altIdentifier/issn/1875-9521info:eu-repo/semantics/altIdentifier/eissn/1875-953XPID2021-122136OB-C22info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122136OB-C22Attribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:10256/273062026-05-29T05:05:01Z
dc.title.none.fl_str_mv Using search algorithm statistics for assessing maze and puzzle difficulty
title Using search algorithm statistics for assessing maze and puzzle difficulty
spellingShingle Using search algorithm statistics for assessing maze and puzzle difficulty
Valenzuela Muñoz, Elio Matías
Algorismes computacionals
Computer algorithms
Videojocs
Video games
Simulació per ordinador
Computer simulation
title_short Using search algorithm statistics for assessing maze and puzzle difficulty
title_full Using search algorithm statistics for assessing maze and puzzle difficulty
title_fullStr Using search algorithm statistics for assessing maze and puzzle difficulty
title_full_unstemmed Using search algorithm statistics for assessing maze and puzzle difficulty
title_sort Using search algorithm statistics for assessing maze and puzzle difficulty
dc.creator.none.fl_str_mv Valenzuela Muñoz, Elio Matías
Schaa, Hans
Barriga, Nicolas A.
Patow, Gustavo
author Valenzuela Muñoz, Elio Matías
author_facet Valenzuela Muñoz, Elio Matías
Schaa, Hans
Barriga, Nicolas A.
Patow, Gustavo
author_role author
author2 Schaa, Hans
Barriga, Nicolas A.
Patow, Gustavo
author2_role author
author
author
dc.contributor.none.fl_str_mv Agencia Estatal de Investigación
dc.subject.none.fl_str_mv Algorismes computacionals
Computer algorithms
Videojocs
Video games
Simulació per ordinador
Computer simulation
topic Algorismes computacionals
Computer algorithms
Videojocs
Video games
Simulació per ordinador
Computer simulation
description A video game’s difficulty has a large impact on player engagement. For instance, it is crucial in some genres to give the players a challenge difficult enough without frustrating them. We propose a simple method for assessing game-level difficulty as a precursor to adapting it to a specific player. In particular, we propose using simple performance metrics of algorithms such as A* and Breadth-First Search (BFS) as a proxy for the difficulty of puzzles. We performed user studies using a 2D maze simulator and a Sokoban game implementation; both built into the Unity game engine. We show that, for 2D mazes generated by Binary Space Partitioning, the number of nodes expanded by BFS highly correlates with the number of steps a human player takes to reach the goal. For Sokoban puzzles, the closed list length of an A* search is highly correlated to perceived difficulty and the number of movements a human player takes to solve the puzzle. These results show that simple metrics are probably good enough to assess a given level’s difficulty, which is a first step towards being able to personalize the difficulty of a maze or a puzzle to a particular player
publishDate 2025
dc.date.none.fl_str_mv 2025
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
peer-reviewed
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10256/27306
http://hdl.handle.net/10256/27306
url http://hdl.handle.net/10256/27306
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.entcom.2025.100925
info:eu-repo/semantics/altIdentifier/issn/1875-9521
info:eu-repo/semantics/altIdentifier/eissn/1875-953X
PID2021-122136OB-C22
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-122136OB-C22
dc.rights.none.fl_str_mv Attribution-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Entertainment Computing, 2025, vol. 53, art. núm. 100925
Articles publicats (D-IMA)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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