Advertisement

Progress in RoboCup Revisited: The State of Soccer Simulation 2D

  • Thomas Gabel
  • Egbert Falkenberg
  • Eicke Godehardt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9776)

Abstract

A remarkable feature of RoboCup’s soccer simulation leagues is their ability to quantify and prove the exact progress made over years. In this paper, we present and discuss the results of an extensive empirical study of the progress and the currently reached state of 2D soccer simulation. Our main finding is that the current decade has witnessed a continuous and statistically significant improvement of the overall level of play, but that the magnitude of the progress made has dropped clearly when compared to the previous decade. In accordance to this, we envision possible future prospects for the 2D league that might respond to our empirical findings.

Notes

Acknowledgements

The authors would like to thank Bernd Dankert for his support in conducting the empirical experiments.

References

  1. 1.
    Akiyama, H., Dorer, K., Lau, N.: On the progress of soccer simulation leagues. In: Bianchi, R.A.C., Akin, H.L., Ramamoorthy, S., Sugiura, K. (eds.) RoboCup 2014. LNCS (LNAI), vol. 8992, pp. 599–610. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-18615-3_49CrossRefGoogle Scholar
  2. 2.
    Budden, D., Wang, P., Obst, O., Prokopenko, M.: RoboCup simulation leagues: enabling replicable and robus investigation of complex robotic systems. IEEE Robot. Autom. Mag. 3(22), 140–146 (2015)CrossRefGoogle Scholar
  3. 3.
    Gabel, T., Riedmiller, M.: On progress in RoboCup: the simulation league showcase. In: Ruiz-del-Solar, J., Chown, E., Plöger, P.G. (eds.) RoboCup 2010. LNCS (LNAI), vol. 6556, pp. 36–47. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-20217-9_4CrossRefGoogle Scholar
  4. 4.
    Johnson, R., Wichern, D.: Applied Multivariate Statistical Analysis. Prentice Hall, Upper Saddle River (1998)zbMATHGoogle Scholar
  5. 5.
    Kalyanakrishnan, S., Liu, Y., Stone, P.: Half field offense in RoboCup soccer: a multiagent reinforcement learning case study. In: Lakemeyer, G., Sklar, E., Sorrenti, D.G., Takahashi, T. (eds.) RoboCup 2006. LNCS (LNAI), vol. 4434, pp. 72–85. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-74024-7_7CrossRefGoogle Scholar
  6. 6.
    Noda, I.: Soccer server: a simulator of RoboCup. In: Proceedings of the AI Symposium 1995, pp. 29–34. Japanese Society for Artificial Intelligence (1995)Google Scholar
  7. 7.
    Perl, J., Grunz, A., Memmert, D.: Tactics analysis in soccer - an advanced approach. Int. J. Comput. Sci. Sport 12, 33–44 (2013)Google Scholar
  8. 8.
    Stone, P., Sutton, R., Kuhlmann, G.: Reinforcement learning for RoboCup-soccer keepaway. Adapt. Behav. 3(13), 165–188 (2005)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Thomas Gabel
    • 1
  • Egbert Falkenberg
    • 1
  • Eicke Godehardt
    • 1
  1. 1.Faculty of Computer Science and EngineeringFrankfurt University of Applied SciencesFrankfurt am MainGermany

Personalised recommendations