Thomas Smith
ABSTRACT
The construction of dungeons in typical action-adventure computer games entails composing a complex arrangement of structural and temporal dependencies. It is not simple to generate dungeons with correct lock-and-key structures. In this paper we sketch a controllable approach to building graph-based models of acyclic dungeon levels via declarative constraint solving, that is capable of satisfying a range of hard gameplay and design constraints. We use a quantitative expressive range analysis to characterise the initial output of the system, present an example of the degree to which the output may be altered, and show a comparison with an alternate approach.
- Alexander Baldwin, Steve Dahlskog, Jose M. Font, and Johan Holmberg. 2017. Towards Pattern-based Mixed-initiative Dungeon Generation. In Proceedings of the 12th International Conference on the Foundations of Digital Games (FDG '17). ACM, New York, NY, USA, Article 74, 10 pages. Google Scholar
Digital Library
- Mark Brown. 2017. How my Boss Key dungeon graphs work. (August 2017). https://www.patreon.com/posts/how-my-boss-key-13801754 Accessed: 2018-06-29.Google Scholar
- Eric Butler, Adam M Smith, Yun-En Liu, and Zoran Popovic. 2013. A mixed-initiative tool for designing level progressions in games. In Proceedings of the 26th annual ACM symposium on User interface software and technology. ACM, 377--386. Google ScholarDigital Library
- Kate Compton, Adam Smith, and Michael Mateas. 2012. Anza island: Novel gameplay using ASP. In Proceedings of the The third workshop on Procedural Content Generation in Games. ACM, 13. Google ScholarDigital Library
- Michael Cook, Jeremy Gow, and Simon Colton. 2016. Danesh: Helping bridge the gap between procedural generators and their output. In Proceedings of the 7th International Workshop on Procedural Content Generation in Games. ACM.Google Scholar
- Joris Dormans. 2010. Adventures in level design: generating missions and spaces for action adventure games. In Proceedings of the 2010 workshop on procedural content generation in games. ACM, 1. Google ScholarDigital Library
- Joris Dormans. 2011. Level design as model transformation: a strategy for automated content generation. In Proceedings of the 2nd International Workshop on Procedural Content Generation in Games. ACM. Google ScholarDigital Library
- Joris Dormans. 2017. Cyclic Generation. In Procedural Generation in Game Design. CRC Press, 83--96.Google Scholar
- Daniel Foreman-Mackey. 2016. corner.py: Scatterplot matrices in Python. The Journal of Open Source Software 24 (2016).Google Scholar
- Norbert Heijne and Sander Bakkes. 2017. Procedural Zelda: APCG Environment for Player Experience Research. In Proceedings of the 12th International Conference on the Foundations of Digital Games (FDG '17). ACM, New York, NY, USA, Article 11, 10 pages. Google ScholarDigital Library
- Britton Horn, Steve Dahlskog, Noor Shaker, Gillian Smith, and Julian Togelius. 2014. A comparative evaluation of procedural level generators in the mario ai framework. (2014).Google Scholar
- Daniël Karavolos, Anders Bouwer, and Rafael Bidarra. 2015. Mixed-Initiative Design of Game Levels: Integrating Mission and Space into Level Generation.. In FDG.Google Scholar
- Rebecca Lavender. 2016. The Zelda Dungeon Generator: Adopting Generative Grammars to Create Levels for Action-Adventure Games. (2016).Google Scholar
- Mark J Nelson and Adam M Smith. 2016. ASP with applications to mazes and levels. In Procedural Content Generation in Games. Springer, 143--157.Google Scholar
- Xenija Neufeld, Sanaz Mostaghim, and Diego Perez-Liebana. 2015. Procedural level generation with Answer Set Programming for General Video Game playing. In Computer Science and Electronic Engineering Conference (CEEC), 2015 7th. IEEE, 207--212.Google ScholarCross Ref
- Anthony J Smith and Joanna J Bryson. 2014. A logical approach to building dungeons: Answer Set Programming for hierarchical procedural content generation in roguelike games. In Proceedings of the 50th Anniversary Convention of the AISB.Google Scholar
- Adam M. Smith, Erik Andersen, Michael Mateas, and Zoran Popović. 2012. A Case Study of Expressively Constrainable Level Design Automation Tools for a Puzzle Game. In Proceedings of the International Conference on the Foundations of Digital Games (FDG '12). ACM, New York, NY, USA, 156--163. Google ScholarDigital Library
- Adam M Smith and Michael Mateas. 2011. Answer set programming for procedural content generation: A design space approach. IEEE Transactions on Computational Intelligence and AI in Games 3, 3 (2011), 187--200.Google ScholarCross Ref
- Gillian Smith and Jim Whitehead. 2010. Analyzing the expressive range of a level generator. In Proceedings of the 2010 Workshop on Procedural Content Generation in Games. ACM. Google ScholarDigital Library
- Adam J Summerville, Morteza Behrooz, Michael Mateas, and Arnav Jhala. 2015. The learning of zelda: Data-driven learning of level topology. In Proceedings of the FDG workshop on Procedural Content Generation in Games.Google Scholar
- Valtchan Valtchanov and Joseph Alexander Brown. 2012. Evolving dungeon crawler levels with relative placement. In Proceedings of the Fifth International C* Conference on Computer Science and Software Engineering. ACM, 27--35. Google ScholarDigital Library
- Roland Van der Linden, Ricardo Lopes, and Rafael Bidarra. 2013. Designing procedurally generated levels. In Proceedings of the the second workshop on Artificial Intelligence in the Game Design Process.Google Scholar
- Roland van der Linden, Ricardo Lopes, and Rafael Bidarra. 2014. Procedural generation of dungeons. IEEE Transactions on Computational Intelligence and AI in Games 6, 1 (2014), 78--89.Google ScholarCross Ref
Index Terms
- Graph-based generation of action-adventure dungeon levels using answer set programming
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