Skip to main content
SpringerLink
Log in

Exploring the Visual Styles of Arcade Game Assets

  • Conference paper
  • First Online:
Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9596))

Abstract

This paper describes a method for evolving assets for video games based on their visuals properties. Focusing on assets for a space shooter game, a genotype consisting of turtle commands is transformed into a spaceship image composed of human-authored sprite components. Due to constraints on the final spaceships’ plausibility, the paper investigates two-population constrained optimization and constrained novelty search methods. A sample of visual styles is tested, each a combination of visual metrics which primarily evaluate balance and shape complexity. Experiments with constrained optimization of a visual style demonstrate that a visually consistent set of spaceships can be generated, while experiments with constrained novelty search demonstrate that several distinct visual styles can be discovered by exploring along select, or all, visual dimensions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Due to stochasticity, the chosen clusters are the best of 100 independent clustering attempts.

References

  1. Liapis, A., Yannakakis, G.N., Togelius, J.: Computational game creativity. In: Proceedings of the Fifth International Conference on Computational Creativity (2014)

    Google Scholar 

  2. Champandard, A.: EA investing in the next-generation with proceduralism post-SSX. http://aigamedev.com/open/teaser/investing-in-procedural/. Accessed 11 January 2016

  3. Entertainment, B.: What is Diablo III? http://us.battle.net/d3/en/game/what-is. Accessed 11 January 2016

  4. Togelius, J., Nelson, M.J., Liapis, A.: Characteristics of generatable games. In: Proceedings of the FDG Workshop on Procedural Content Generation (2014)

    Google Scholar 

  5. Arnheim, R.: Art and Visual Perception: A Psychology of the Creative Eye, Revised and expanded edn. University of California Press, Berkeley (2004)

    Google Scholar 

  6. Kimbrough, S.O., Koehler, G.J., Lu, M., Wood, D.H.: On a feasible-infeasible two-population (FI-2Pop) genetic algorithm for constrained optimization: Distance tracing and no free lunch. Eur. J. Oper. Res. 190(2), 310–327 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  7. Liapis, A., Yannakakis, G.N., Togelius, J.: Enhancements to constrained novelty search: Two-population novelty search for generating game content. In: Proceedings of Genetic and Evolutionary Computation Conference (2013)

    Google Scholar 

  8. Lehman, J., Stanley, K.O.: Revising the evolutionary computation abstraction: Minimal criteria novelty search. In: Proceedings of the Genetic and Evolutionary Computation Conference (2010)

    Google Scholar 

  9. Preuss, M., Liapis, A., Togelius, J.: Searching for good and diverse game levels. In: Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG) (2014)

    Google Scholar 

  10. Smith, G., Whitehead, J.: Analyzing the expressive range of a level generator. In: Proceedings of the FDG workshop on Procedural Content Generation (2010)

    Google Scholar 

  11. Togelius, J., Yannakakis, G.N., Stanley, K.O., Browne, C.: Search-based procedural content generation: a taxonomy and survey. IEEE Trans. Comput. Intell. AI Games 3(3), 172–186 (2011)

    Article  Google Scholar 

  12. Liapis, A., Yannakakis, G.N., Togelius, J.: Towards a generic method of evaluating game levels. In: Proceedings of the AAAI Artificial Intelligence for Interactive Digital Entertainment Conference (2013)

    Google Scholar 

  13. Lara-Cabrera, R., Cotta, C., Fernández-Leiva, A.J.: A procedural balanced map generator with self-adaptive complexity for the real-time strategy game planet wars. In: Esparcia-Alcázar, A.I. (ed.) EvoApplications 2013. LNCS, vol. 7835, pp. 274–283. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  14. Sorenson, N., Pasquier, P., DiPaola, S.: A generic approach to challenge modeling for the procedural creation of video game levels. IEEE Trans. Comput. Intell. AI Games 3(3), 229–244 (2011)

    Article  Google Scholar 

  15. Liapis, A., Yannakakis, G.N., Togelius, J.: Sentient Sketchbook: Computer-aided game level authoring. In: Proceedings of the 8th Conference on the Foundations of Digital Games (2013)

    Google Scholar 

  16. Howlett, A., Colton, S., Browne, C.: Evolving pixel shaders for the prototype video game subversion. In: Proceedings of the AI and Games Symposium (AISB 2010) (2010)

    Google Scholar 

  17. Hastings, E.J., Guha, R.K., Stanley, K.O.: Automatic content generation in the galactic arms race video game. IEEE Trans. Comput. Intell. AI Games 1(4), 245–263 (2009)

    Article  Google Scholar 

  18. Risi, S., Lehman, J., D’Ambrosio, D., Hall, R., Stanley, K.O.: Combining search-based procedural content generation and social gaming in the petalz video game. In: Proceedings of Artificial Intelligence and Interactive Digital Entertainment Conference (2012)

    Google Scholar 

  19. Liapis, A., Yannakakis, G.N., Togelius, J.: Adapting models of visual aesthetics for personalized content creation. IEEE Trans. Comput. Intell. AI Games 4(3), 213–228 (2012)

    Article  Google Scholar 

  20. Michalewicz, Z.: Do not kill unfeasible individuals. In: Proceedings of the Intelligent Information Systems Workshop (1995)

    Google Scholar 

  21. Coello Coello, C.A.: Constraint-handling techniques used with evolutionary algorithms. In: Proceedings of the Genetic and Evolutionary Computation Conference, ACM (2010)

    Google Scholar 

  22. Liapis, A., Yannakakis, G.N., Togelius, J.: Neuroevolutionary constrained optimization for content creation. In: Proceedings of the IEEE Conference on Computational Intelligence and Games (2011)

    Google Scholar 

  23. Lehman, J., Stanley, K.O.: Abandoning objectives: Evolution through the search for novelty alone. Evol. Comput. 19(2), 189–223 (2011)

    Article  Google Scholar 

  24. Liapis, A., Yannakakis, G.N., Togelius, J.: Constrained novelty search: a study on game content generation. Evol. Comput. 23(1), 101–129 (2015)

    Article  Google Scholar 

  25. Dunn, O.: Multiple comparisons among means. J. Am. Stat. Assoc. 56, 52–64 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  26. Shapiro, S.S., Wilk, M.B.: Analysis of variance test for normality (complete samples). Biometrika (1965)

    Google Scholar 

  27. Dunn, J.C.: A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. J. Cybern. 3(3), 32–57 (1973)

    Article  MathSciNet  MATH  Google Scholar 

  28. Correia, J., Machado, P., Romero, J., Carballal, A.: Evolving figurative images using expression-based evolutionary art. In: Proceedings of the International Conference on Computational Creativity (2013)

    Google Scholar 

  29. Liapis, A., Martínez, H.P., Togelius, J., Yannakakis, G.N.: Transforming exploratory creativity with DeLeNoX. In: Proceedings of the International Conference on Computational Creativity (2013)

    Google Scholar 

Download references

Acknowledgements

The sprite components used to construct the spaceships are freely licensed art assets found in OpenGameArt (http://opengameart.org/content/modular-ships) and are not the intellectual property of the author. The research was supported, in part, by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).

Author information

Authors and Affiliations

  1. Institute of Digital Games, University of Malta, Msida, Malta

    Antonios Liapis

Authors
  1. Antonios Liapis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Antonios Liapis .

Editor information

Editors and Affiliations

  1. University of Kent, Canterbury, United Kingdom

    Colin Johnson

  2. RMIT University, Melbourne, Victoria, Australia

    Vic Ciesielski

  3. University of Coimbra, Coimbra, Portugal

    João Correia

  4. University of Coimbra, Coimbra, Portugal

    Penousal Machado

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Liapis, A. (2016). Exploring the Visual Styles of Arcade Game Assets. In: Johnson, C., Ciesielski, V., Correia, J., Machado, P. (eds) Evolutionary and Biologically Inspired Music, Sound, Art and Design. EvoMUSART 2016. Lecture Notes in Computer Science(), vol 9596. Springer, Cham. https://doi.org/10.1007/978-3-319-31008-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-31008-4_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-31007-7

  • Online ISBN: 978-3-319-31008-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation