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European Conference on the Applications of Evolutionary Computation

EvoApplications 2016: Applications of Evolutionary Computation pp 653–668Cite as

A Spatially-Structured PCG Method for Content Diversity in a Physics-Based Simulation Game

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9597))

Abstract

This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of different levels of difficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n-body problem, a classical problem in the field of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the difficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e., intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of maps with different difficulty in Gravityvolve!.

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Notes

  1. 1.

    http://planetwars.aichallenge.org/.

  2. 2.

    Wikipedia. Accessed on 17th of January, 2016.

References

  1. Lara-Cabrera, R., Cotta, C., Fernández-Leiva, A.: An analysis of the structure and evolution of the scientific collaboration network of computer intelligence in games. Phys. A Stat. Mech. Appl. 395, 523–536 (2014)

    Article  Google Scholar 

  2. Togelius, J., Champandard, A.J., Lanzi, P.L., Mateas, M., Paiva, A., Preuss, M., Stanley, K.O.: Procedural content generation: goals, challenges and actionable steps. In: Lucas, S.M., Mateas, M., Preuss, M., Spronck, P., Togelius, J. (eds.) Artificial and Computational Intelligence in Games. Dagstuhl Follow-Ups, vol. 6, pp. 61–75. Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik (2013)

    Google Scholar 

  3. Hendrikx, M., Meijer, S., Van Der Velden, J., Iosup, A.: Procedural content generation for games: a survey. ACM Trans. Multimed. Comput. Commun. Appl. (TOMCCApP) 9(1), 1–22 (2013)

    Article  Google Scholar 

  4. Shaker, N., Togelius, J., Nelson, M.J.: Procedural Content Generation in Games: A Textbook and an Overview of Current Research. Springer, New York (2014)

    Google Scholar 

  5. Rivello, S.A.: Developing physics-based games with adobe flash professional EDGE, article 7, April 2010. Accessed 15 Jan 2015

    Google Scholar 

  6. Shaker, M., Sarhan, M.H., Naameh, O.A., Shaker, N., Togelius, J.: Automatic generation and analysis of physics-based puzzle games. In: 2013 IEEE Conference on Computational Inteligence in Games (CIG), Niagara Falls, ON, Canada, 11–13 August 2013, pp. 1–8. IEEE (2013)

    Google Scholar 

  7. Preuss, M., Liapis, A., Togelius, J.: Searching for good and diverse game levels. In: 2014 IEEE Conference on Computational Intelligence and Games (CIG), pp. 1–8, August 2014

    Google Scholar 

  8. Lara-Cabrera, R., Fernández-Leiva, A.J.: Gravityvolve!

    Google Scholar 

  9. 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 

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

    Article  Google Scholar 

  11. Yannakakis, G., Togelius, J.: A panorama of artificial and computational intelligence in games. IEEE Trans. Comput. Intell. AI Games PP(99), 1 (2014)

    Google Scholar 

  12. Shaker, N., Yannakakis, G.N., Togelius, J.: Towards automatic personalized content generation for platform games. In: AIIDE (2010)

    Google Scholar 

  13. Pedersen, C., Togelius, J., Yannakakis, G.N.: Modeling player experience in super mario bros. In: IEEE Symposium on Computational Intelligence and Games, 2009, CIG 2009, pp. 132–139. IEEE (2009)

    Google Scholar 

  14. Togelius, J., Preuss, M., Yannakakis, G.N.: Towards multiobjective procedural map generation. In: Proceedings of the 2010 Workshop on Procedural Content Generation in Games, vol. 3. ACM (2010)

    Google Scholar 

  15. Togelius, J., Preuss, M., Beume, N., Wessing, S., Hagelback, J., Yannakakis, G.N.: Multiobjective exploration of the Starcraft map space. In: 2010 IEEE Symposium on Computational Intelligence and Games (CIG), pp. 265–272. IEEE (2010)

    Google Scholar 

  16. Togelius, J., De Nardi, R., Lucas, S.M.: Towards automatic personalised content creation for racing games. In: IEEE Symposium on Computational Intelligence and Games, 2007, CIG 2007, pp. 252–259. IEEE (2007)

    Google Scholar 

  17. Ferreira, L., Toledo, C.: A search-based approach for generating angry birds levels. In: 2014 IEEE Conference on Computational Intelligence and Games (CIG), pp. 1–8 (2014)

    Google Scholar 

  18. Lara-Cabrera, R., Cotta, C., Fernández-Leiva, A.: On balance and dynamism in procedural content generation with self-adaptive evolutionary algorithms. Nat. Comput. 13(2), 157–168 (2014)

    Article  MathSciNet  Google Scholar 

  19. Lara-Cabrera, R., Cotta, C.: Geometrical vs. topological measures for the evolution of aesthetic maps in a RTS game. Entertainment Comput. 5(4), 251–258 (2014)

    Article  Google Scholar 

  20. Toussaint, G.T.: A graph-theoretic primal sketch. In: Toussaint, G.T. (ed.) Computational Morphology, pp. 229–260. Elsevier, Amsterdam (1988)

    Google Scholar 

  21. Frade, M., de Vega, F.F., Cotta, C.: Evolution of artificial terrains for video games based on obstacles edge length. In: 2010 IEEE Congress on Evolutionary Computation (CEC), pp. 1–8. IEEE (2010)

    Google Scholar 

  22. Frade, M., de Vega, F., Cotta, C.: Automatic evolution of programs for procedural generation of terrains for video games. Soft. Comput. 16(11), 1893–1914 (2012)

    Article  Google Scholar 

  23. Hom, V., Marks, J.: Automatic design of balanced board games. In: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), pp. 25–30 (2007)

    Google Scholar 

  24. 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 

  25. Hastings, E.J., Guha, R.K., Stanley, K.O.: Evolving content in the Galactic Arms Race video game. In: IEEE Symposium on Computational Intelligence and Games, 2009, CIG 2009, pp. 241–248. IEEE (2009)

    Google Scholar 

  26. Collins, K.: An introduction to procedural music in video games. Contemp. Music Rev. 28(1), 5–15 (2009)

    Article  Google Scholar 

  27. Font, J.M., Mahlmann, T., Manrique, D., Togelius, J.: A card game description language. In: Esparcia-Alcázar, A.I. (ed.) EvoApplications 2013. LNCS, vol. 7835, pp. 254–263. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  28. Onuczko, C., Szafron, D., Schaeffer, J., Cutumisu, M., Siegel, J., Waugh, K., Schumacher, A.: Automatic story generation for computer role-playing games. In: AIIDE, pp. 147–148 (2006)

    Google Scholar 

  29. van der Linden, R., Lopes, R., Bidarra, R.: Procedural generation of dungeons. IEEE Trans. Comput. Intell. AI Games 6(1), 78–89 (2014)

    Article  Google Scholar 

  30. Ashlock, D., Lee, C., McGuinness, C.: Search-based procedural generation of maze-like levels. IEEE Trans. Comput. Intell. AI Games 3(3), 260–273 (2011)

    Article  Google Scholar 

  31. Plans, D., Morelli, D.: Experience-driven procedural music generation for games. IEEE Trans. Comput. Intell. AI Games 4(3), 192–198 (2012)

    Article  Google Scholar 

  32. The physical travelling salesman problem. Accessed 10 December 2015

    Google Scholar 

  33. Perez, D., Powley, E.J., Whitehouse, D., Rohlfshagen, P., Samothrakis, S., Cowling, P.I., Lucas, S.M.: Solving the physical traveling salesman problem: tree search and macro actions. IEEE Trans. Comput. Intellig. AI Games 6(1), 31–45 (2014)

    Article  Google Scholar 

  34. Powley, E., Whitehouse, D., Cowling, P.: Monte carlo tree search with macro-actions and heuristic route planning for the physical travelling salesman problem. In: IEEE Conference on Computational Intelligence and Games (CIG), September 2012, pp. 234–241 (2012)

    Google Scholar 

  35. Browne, C., Powley, E., Whitehouse, D., Lucas, S., Cowling, P., Rohlfshagen, P., Tavener, S., Perez, D., Samothrakis, S., Colton, S.: A survey of monte carlo tree search methods. IEEE Trans. Comput. Intell. AI Games 4(1), 1–43 (2012)

    Article  Google Scholar 

  36. Kortemeyer, G., Tan, P., Schirra, S.: A slower speed of light: developing intuition about special relativity with games. In: International Conference on the Foundations of Digital Games, Chania, Crete, Greece, 14–17 May 2013, pp. 400–402 (2013)

    Google Scholar 

  37. Aarseth, S.J., Aarseth, S.J.: Gravitational N-Body Simulations: Tools and Algorithms. Cambridge University Press, Cambridge (2003)

    Book  MATH  Google Scholar 

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Acknowledgments

This work has been partially funded by Spanish MICINN under project UMA-EPHEMECH (http://blog.epheme.ch) (TIN2014-56494-C4-1-P), by Junta de Andalucía under project P10-TIC-6083 (DNEMESIS (http://dnemesis.lcc.uma.es/wordpress/)) and Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

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Authors and Affiliations

  1. Departmento de Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain

    Raúl Lara-Cabrera & Antonio J. Fernández-Leiva

  2. Departamento de Arquitectura de Computadores, Universidad de Málaga, Málaga, Spain

    Alejandro Gutierrez-Alcoba

Authors
  1. Raúl Lara-Cabrera
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  2. Alejandro Gutierrez-Alcoba
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  3. Antonio J. Fernández-Leiva
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Corresponding author

Correspondence to Antonio J. Fernández-Leiva .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Aalborg University, Copenhagen, Denmark

    Paolo Burelli

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Lara-Cabrera, R., Gutierrez-Alcoba, A., Fernández-Leiva, A.J. (2016). A Spatially-Structured PCG Method for Content Diversity in a Physics-Based Simulation Game. In: Squillero, G., Burelli, P. (eds) Applications of Evolutionary Computation. EvoApplications 2016. Lecture Notes in Computer Science(), vol 9597. Springer, Cham. https://doi.org/10.1007/978-3-319-31204-0_42

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  • DOI: https://doi.org/10.1007/978-3-319-31204-0_42

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-31204-0

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