research-article

Procedural generation of dungeons’ maps and locked-door missions through an evolutionary algorithm validated with players

Authors:

Leonardo Tortoro Pereira,

Paulo Victor de Souza Prado,

Rafael Miranda Lopes,

Claudio Fabiano Motta ToledoAuthors Info & Claims

Volume 180, Issue C

https://doi.org/10.1016/j.eswa.2021.115009

Published: 15 October 2021 Publication History

Highlights

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Single Evolutionary Algorithm encoding able to create procedural dungeon and mission.

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Accurately create feasible dungeons of many sizes, linearity and locked-door puzzles.

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A game prototype was developed and used for experiments with players.

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Users evaluated the created content as human-made and fun as classic game levels.

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Generated content allows a more complete exploration when compared to classic levels.

Abstract

The present research introduces an evolutionary algorithm able to procedurally generate dungeon maps containing locked door missions. The evolutionary algorithm evolves a tree structure, which encodes dungeons, aiming to generate levels close to the input configuration provided by a game designer. The tree structure holds information about the number of rooms, connections between them, and their position within a 2D map. The proposed encoding also allows evolving semantic information about the narrative of the game. This is done by feasibly setting keys and locks throughout the dungeons for locked door missions. The generated dungeons are then evaluated computationally and as a proof of concept using an adventure game prototype. A total of 70 players evaluated the contents and the results show that the procedurally generated levels are perceived as more human-made, fun, and difficult than their human-made counterparts for most cases.

References

[1]

C. Adams, H. Parekh, S.J. Louis, Procedural level design using an interactive cellular automata genetic algorithm, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2017, pp. 85–86,.

Digital Library

[2]

E. Adams, Fundamentals of Game Design, 2nd ed., New Riders Publishing, Thousand Oaks, CA, USA, 2009.

[3]

A. Alvarez, S. Dahlskog, J. Font, J. Togelius, Empowering quality diversity in dungeon design with interactive constrained map-elites, in: 2019 IEEE Conference on Games (CoG), 2019, pp. 1–8,.

Digital Library

[4]

Antoniuk, I., & Rokita, P. (2019). Procedural generation of multilevel dungeons for application in computer games using schematic maps and l-system. In R. Bembenik, Ł. Skonieczny, G. Protaziuk, M. Kryszkiewicz, & H. Rybinski (Eds.), Intelligent Methods and Big Data in Industrial Applications (pp. 261–275). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-77604-0_19.

[5]

D. Ashlock, M. Kreitzer, P. Ciancarini, M. Mazzara, A. Messina, A. Sillitti, G. Succi (Eds.), Evolving diverse cellular automata based level maps Proceedings of 6th International Conference in Software Engineering for Defence Applications, Springer International Publishing, Cham, 2020, pp. 10–23.

[6]

D. Ashlock, C. McGuinness, Automatic generation of fantasy role-playing modules, in: 2014 IEEE Conference on Computational Intelligence and Games, 2014, pp. 1–8,.

[7]

D. Ashlock, C. Salge, The riddle of togelby, in: 2019 IEEE Conference on Games (CoG), 2019, pp. 1–8.

[8]

A. Baldwin, S. Dahlskog, J.M. Font, J. Holmberg, Mixed-initiative procedural generation of dungeons using game design patterns, in: 2017 IEEE Conference on Computational Intelligence and Games (CIG), 2017, pp. 25–32,.

Digital Library

[9]

A. Calvin, N. Michael, The quest in a generated world, in: DiGRA & #3907 - Proceedings of the 2007 DiGRA International Conference: Situated Play, The University of Tokyo, 2007.

[10]

Dahlskog, S., Togelius, J., & Björk, S. (2015). Patterns, dungeons and generators. In FDG.

[11]

J. Dormans, S. Bakkes, Generating missions and spaces for adaptable play experiences, IEEE Transactions on Computational Intelligence and AI in Games 3 (2011) 216–228,.

[12]

L.N. Ferreira, C.F.M. Toledo, Tanager: A generator of feasible and engaging levels for angry birds, IEEE Transactions on Games 10 (2018) 304–316,.

[13]

J.M. Font, R. Izquierdo, D. Manrique, J. Togelius, Constrained level generation through grammar-based evolutionary algorithms, in: G. Squillero, P. Burelli (Eds.), Applications of Evolutionary Computation, Springer International Publishing, Cham, 2016, pp. 558–573.

[14]

Games, F. (2016a). Civilization vi. https://www.civilization.com/.

[15]

Games, H. (2016b). No man’s sky. http://www.no-mans-sky.com/about/.

[16]

M.C. Green, A. Khalifa, A. Alsoughayer, D. Surana, A. Liapis, J. Togelius, Two-step constructive approaches for dungeon generation, in: Proceedings of the 14th International Conference on the Foundations of Digital Games FDG -19, Association for Computing Machinery, New York, NY, USA, 2019,.

Digital Library

[17]

Hendrikx, M., Meijer, S., Van Der Velden, J., & Iosup, A. (2013). Procedural content generation for games: A survey. (pp. 1:1–1:22). New York, NY, USA: ACM volume 9. https://doi.org/10.1145/2422956.2422957.

[18]

I. Horswill, L. Foged, Fast procedural level population with playability constraints, in: Proceedings of the Eighth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment AIIDE’12, AAAI Press, 2012, pp. 20–25.

[19]

Iosup, A. (2011). Poggi: Generating puzzle instances for online games on grid infrastructures. (pp. 158–171). Chichester, UK: John Wiley and Sons Ltd. volume 23. https://doi.org/10.1002/cpe.1638.

[20]

A. Khalifa, D. Perez-Liebana, S.M. Lucas, J. Togelius, General video game level generation, Proceedings of the Genetic and Evolutionary Computation Conference 2016 GECCO, ’16, ACM, New York, NY, USA, 2016, pp. 253–259,.

Digital Library

[21]

A. Liapis, Multi-segment evolution of dungeon game levels, Proceedings of the Genetic and Evolutionary Computation Conference GECCO, ’17, ACM, New York, NY, USA, 2017, pp. 203–210,.

Digital Library

[22]

A. Liapis, G.N. Yannakakis, M.J. Nelson, M. Preuss, R. Bidarra, Orchestrating game generation, IEEE Transactions on Games 11 (2019) 48–68,.

[23]

D. Lora, A.A. Sánchez-Ruiz, P.A. González-Calero, M.A. Gómez-Martín, Dynamic difficulty adjustment in tetris, in: The Twenty-Ninth International Flairs Conference, 2016.

[24]

Miyamoto, S., & Tezuka, T. (1986). The legend of zelda series. http://www.zelda.com/.

[25]

Newzoo (2020). Newzoo global games market report 2020: Light version. https://newzoo.com/insights/trend-reports/newzoo-global-games-market-report-2020-light-version/.

[26]

L.T. Pereira, P.V.S. Prado, C. Toledo, Evolving dungeon maps with locked door missions, in: 2018 IEEE Congress on Evolutionary Computation (CEC), 2018, pp. 1–8,.

Digital Library

[27]

S. Rogers, Level Up! The Guide to Great Video Game Design, (2nd ed.)., Wiley Publishing, 2014.

[28]

V. Valtchanov, J.A. Brown, Evolving dungeon crawler levels with relative placement, Proceedings of the Fifth International C* Conference on Computer Science and Software Engineering C3S2E, ’12, ACM, New York, NY, USA, 2012, pp. 27–35,.

Digital Library

[29]

B. von Rymon Lipinski, S. Seibt, J. Roth, D. Abé, Level graph - incremental procedural generation of indoor levels using minimum spanning trees, in: 2019 IEEE Conference on Games (CoG), 2019, pp. 1–7,.

Digital Library

[30]

J.C.F.D. Winter, D. Dodou, Five-point likert items: t test versus mann-whitney-wilcoxon, Practical Assessment, Research & Evaluation, 2010, p. 11.

Cited By

Zamorano MDomingo ÁCetina CSarro F(2024)Game Software Engineering: A Controlled Experiment Comparing Automated Content Generation TechniquesProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686690(302-313)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686690
Dumont FRiff MLi XHandl J(2024)2-Step Evolutionary Algorithm for the generation of dungeons with lock door missions using horizontal symmetryProceedings of the Genetic and Evolutionary Computation Conference10.1145/3638529.3654153(1210-1218)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638529.3654153
Gerhold MTijben K(2023)Computer Aided Content Generation – A Gloomhaven Case StudyProceedings of the 18th International Conference on the Foundations of Digital Games10.1145/3582437.3587196(1-10)Online publication date: 12-Apr-2023
https://dl.acm.org/doi/10.1145/3582437.3587196

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Information

Published In

cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 180, Issue C

Oct 2021

596 pages

ISSN:0957-4174

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Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 15 October 2021

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Cited By

Zamorano MDomingo ÁCetina CSarro F(2024)Game Software Engineering: A Controlled Experiment Comparing Automated Content Generation TechniquesProceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement10.1145/3674805.3686690(302-313)Online publication date: 24-Oct-2024
https://dl.acm.org/doi/10.1145/3674805.3686690
Dumont FRiff MLi XHandl J(2024)2-Step Evolutionary Algorithm for the generation of dungeons with lock door missions using horizontal symmetryProceedings of the Genetic and Evolutionary Computation Conference10.1145/3638529.3654153(1210-1218)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638529.3654153
Gerhold MTijben K(2023)Computer Aided Content Generation – A Gloomhaven Case StudyProceedings of the 18th International Conference on the Foundations of Digital Games10.1145/3582437.3587196(1-10)Online publication date: 12-Apr-2023
https://dl.acm.org/doi/10.1145/3582437.3587196

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