Towards Evaluating a Procedural Content Orchestrator Gameplay Data to Differentiate User Profiles
Resumo
We tested a procedural content orchestration algorithm against 15 anonymous users, against 12 different dungeons, played 119 times in total. We used questionnaires to collect data regarding player profiles, and gameplay data to analyze if could identify profiles using them only. Using PCA and clustering techniques, we were able to identify the most important attributes one may collect from gameplay data to analyze and differentiate play-styles. We also identified that the dungeon's characteristics have a heavy influence on analyzing profiles through gameplay, and a more controlled environment may be needed to identify player profiles. More data and further analysis are needed to extract player profiles from gameplay data, but preliminary results show promise.
Palavras-chave:
procedural content generation, player profiling, gameplay metrics evaluation
Referências
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de Lima, E. S., Feijó, B., and Furtado, A. L. (2021). Adaptive branching quests based on automated planning and story arcs. In 2021 20th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), pages 9–18. DOI: 10.1109/SBGames54170.2021.00012.
Doran, J. and Parberry, I. (2011). A prototype quest generator based on a structural analysis of quests from four mmorpgs. In Proceedings of the 2nd International Workshop on Procedural Content Generation in Games, PCGames ’11, New York, NY, USA. Association for Computing Machinery.
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Liapis, A., Yannakakis, G. N., Nelson, M. J., Preuss, M., and Bidarra, R. (2019). Orchestrating game generation. IEEE Transactions on Games, 11(1):48–68.
Lora, D., Sánchez-Ruiz-Granados, A. A., González-Calero, P. A., and Gómez-Martín, M. A. (2016). Dynamic difficulty adjustment in tetris. In FLAIRS Conference. DOI: 10.1007/978-3-030-50353-6_1.
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Melhart, D., Azadvar, A., Canossa, A., Liapis, A., and Yannakakis, G. N. (2019). Your gameplay says it all: Modelling motivation in tom clancy’s the division. CoRR,abs/1902.00040.
Pereira, L. T., Viana, B. M. F., and Toledo, C. F. M. (2022). A system for orchestrating multiple procedurally generated content for different player profiles. IEEE Transactions on Games, pages 1–11.
Rivera-Villicana, J., Zambetta, F., Harland, J., and Berry, M. (2018). Informing a bdi player model for an interactive narrative. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play, CHI PLAY ’18, page 417–428, New York, NY, USA. Association for Computing Machinery.
Togelius, J., Shaker, N., and Nelson, M. J. (2016). Introduction. In Shaker, N., Togelius, J., and Nelson, M. J., editors, Procedural Content Generation in Games: A Textbook and an Overview of Current Research, pages 1–15. Springer.
Vahlo, J., Kaakinen, J., Holm, S., and Koponen, A. (2017). Digital game dynamics preferences and player types: Preferences in game dynamics. Journal of Computer-Mediated Communication, 22.
Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior, 9(6):772–775. PMID: 17201605.
Yee, N. and Ducheneaut, N. (2018). Gamer motivation profiling: Uses and applications. Games User Research, pages 485–490.
Cowley, B., Charles, D., Black, M., and Hickey, R. (2008). Toward an understanding of flow in video games. Computers in Entertainment (CIE), 6:1–27. DOI: 10.1145/1371216.1371223.
de Lima, E. S., Feijó, B., and Furtado, A. L. (2021). Adaptive branching quests based on automated planning and story arcs. In 2021 20th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames), pages 9–18. DOI: 10.1109/SBGames54170.2021.00012.
Doran, J. and Parberry, I. (2011). A prototype quest generator based on a structural analysis of quests from four mmorpgs. In Proceedings of the 2nd International Workshop on Procedural Content Generation in Games, PCGames ’11, New York, NY, USA. Association for Computing Machinery.
Heijne, N. and Bakkes, S. (2017). Procedural zelda: a pcg environment for player experience research. In Proceedings of the 12th International Conference on the Foundations of Digital Games, FDG ’17, New York, NY, USA. Association for Computing Machinery. DOI: 10.1145/3102071.3102091.
Jacko, J. A. (2012). Human-Computer Interaction Handbook: Fundamentals, Evolving Technologies, and Emerging Applications, Third Edition. CRC Press, Inc., Boca Raton, FL, USA, 3rd edition.
Liapis, A., Yannakakis, G. N., Nelson, M. J., Preuss, M., and Bidarra, R. (2019). Orchestrating game generation. IEEE Transactions on Games, 11(1):48–68.
Lora, D., Sánchez-Ruiz-Granados, A. A., González-Calero, P. A., and Gómez-Martín, M. A. (2016). Dynamic difficulty adjustment in tetris. In FLAIRS Conference. DOI: 10.1007/978-3-030-50353-6_1.
Loria, E. and Marconi, A. (2018). Player types and player behaviors: Analyzing correlations in an on-the-field gamified system. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play Companion Extended Abstracts, CHI PLAY 2018, Melbourne, VIC, Australia, October 28-31, 2018, pages 531–538. DOI: 10.1145/3270316.3271526.
Melhart, D., Azadvar, A., Canossa, A., Liapis, A., and Yannakakis, G. N. (2019). Your gameplay says it all: Modelling motivation in tom clancy’s the division. CoRR,abs/1902.00040.
Pereira, L. T., Viana, B. M. F., and Toledo, C. F. M. (2022). A system for orchestrating multiple procedurally generated content for different player profiles. IEEE Transactions on Games, pages 1–11.
Rivera-Villicana, J., Zambetta, F., Harland, J., and Berry, M. (2018). Informing a bdi player model for an interactive narrative. In Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play, CHI PLAY ’18, page 417–428, New York, NY, USA. Association for Computing Machinery.
Togelius, J., Shaker, N., and Nelson, M. J. (2016). Introduction. In Shaker, N., Togelius, J., and Nelson, M. J., editors, Procedural Content Generation in Games: A Textbook and an Overview of Current Research, pages 1–15. Springer.
Vahlo, J., Kaakinen, J., Holm, S., and Koponen, A. (2017). Digital game dynamics preferences and player types: Preferences in game dynamics. Journal of Computer-Mediated Communication, 22.
Yee, N. (2006). Motivations for play in online games. CyberPsychology & Behavior, 9(6):772–775. PMID: 17201605.
Yee, N. and Ducheneaut, N. (2018). Gamer motivation profiling: Uses and applications. Games User Research, pages 485–490.
Publicado
07/10/2024
Como Citar
PEREIRA, Leonardo Tórtoro; TEOI, Tyago Yuji; TOLEDO, Claudio Fabiano Motta.
Towards Evaluating a Procedural Content Orchestrator Gameplay Data to Differentiate User Profiles. In: WORKSHOP SOBRE INTERAÇÃO E PESQUISA DE USUÁRIOS NO DESENVOLVIMENTO DE JOGOS (WIPLAY), 3. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 75-86.
DOI: https://doi.org/10.5753/wiplay.2024.245483.
