Skip to main content
SpringerLink
Log in
Book cover

UK Workshop on Computational Intelligence

UKCI 2017: Advances in Computational Intelligence Systems pp 132–144Cite as

A Multiobjective Evolutionary Algorithm Approach for Map Sketch Generation

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 650))

Abstract

In this paper, we present a method to generate map sketches for strategy games using a state of the art many-objective evolutionary algorithm, namely NSGAIII. The map sketch generator proposed in this study outputs a three objective Pareto-front in which all the points are fair and strong in different aspects. The generated map sketch can be used by level designers to create real time strategy maps effectively and/or help them see multiple aspects of a game map simultaneously. The algorithm can also be utilised as a benchmark generator to be used in tests for various cases such as shortest path algorithms and strategy game bots. The results reported in this paper are very promising and promote further study.

This is a preview of subscription content, 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   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
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

Learn about institutional subscriptions

Notes

  1. 1.

    https://www.nomanssky.com.

  2. 2.

    http://us.blizzard.com/en-us/games/sc/.

  3. 3.

    https://ls11-www.cs.uni-dortmund.de/rudolph/hypervolume/start.

References

  1. 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 

  2. Bjork, S., Holopainen, J.: Patterns in Game Design (Game Development Series). Charles River Media Inc., Rockland (2004)

    Google Scholar 

  3. Deb, K., Jain, H.: An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE Trans. Evol. Comput. 18(4), 577–601 (2014)

    Article  Google Scholar 

  4. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    Article  Google Scholar 

  5. Fonseca, C.M., Paquete, L., Lopez-Ibanez, M.: An improved dimension-sweep algorithm for the hypervolume indicator. In: 2006 IEEE International Conference on Evolutionary Computation, pp. 1157–1163, July 2006

    Google Scholar 

  6. Jain, H., Deb, K.: An evolutionary many-objective optimization algorithm using reference-point based nondominated sorting approach, part II: handling constraints and extending to an adaptive approach. IEEE Trans. Evol. Comput. 18(4), 602–622 (2014)

    Article  Google Scholar 

  7. Liapis, A., Yannakakis, G.N., Togelius, J.: Generating map sketches for strategy games. In: Applications of Evolutionary Computation: 16th European Conference, EvoApplications 2013, Vienna, Austria, 3-5 April 2013, pp. 264–273. Springer, Heidelberg (2013)

    Google Scholar 

  8. Seada, H., Deb, K.: U-NSGA-III: a unified evolutionary optimization procedure for single, multiple, and many objectives: proof-of-principle results. In: Evolutionary Multi-Criterion Optimization: 8th International Conference, EMO 2015, Guimarães, Portugal, 29 March–1 April 2015, Part II, pp. 34–49. Springer International Publishing, Cham (2015)

    Google Scholar 

  9. Togelius, J., Preuss, M., Beume, N., Wessing, S., Hagelbäck, J., Yannakakis, G.N.: Multiobjective exploration of the starcraft map space. In: Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, pp. 265–272, August 2010

    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. Intell. AI Games 3(3), 172–186 (2011)

    Article  Google Scholar 

  11. Togelius, J., Preuss, M., Beume, N., Wessing, S., Hagelbäck, J., Yannakakis, G.N., Grappiolo, C.: Controllable procedural map generation via multiobjective evolution. Genet. Program. Evolvable Mach. 14(2), 245–277 (2013). http://dx.doi.org/10.1007/s10710-012-9174-5

  12. Togelius, J., Preuss, M., Yannakakis, G.N.: Towards multiobjective procedural map generation. In: Proceedings of the 2010 Workshop on Procedural Content Generation in Games, PCGames 2010, pp. 3:1–3:8. ACM, New York (2010). http://doi.acm.org/10.1145/1814256.1814259

Download references

Author information

Authors and Affiliations

  1. MEF University, Istanbul, Turkey

    Şafak Topçu

  2. Istanbul Technical University, Istanbul, Turkey

    A. Şima Etaner-Uyar

  3. Graduate School of Science Engineering and Technology, Istanbul Technical University, Istanbul, Turkey

    Şafak Topçu

Authors
  1. Şafak Topçu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Şima Etaner-Uyar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Şafak Topçu .

Editor information

Editors and Affiliations

  1. Xiamen University, Xiamen Shi, Fujian, China

    Fei Chao

  2. Cardiff University, Cardiff, United Kingdom

    Steven Schockaert

  3. Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong

    Qingfu Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Topçu, Ş., Etaner-Uyar, A.Ş. (2018). A Multiobjective Evolutionary Algorithm Approach for Map Sketch Generation. In: Chao, F., Schockaert, S., Zhang, Q. (eds) Advances in Computational Intelligence Systems. UKCI 2017. Advances in Intelligent Systems and Computing, vol 650. Springer, Cham. https://doi.org/10.1007/978-3-319-66939-7_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-66939-7_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66938-0

  • Online ISBN: 978-3-319-66939-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation