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UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions

  • Patrick MacAlpineEmail author
  • Peter Stone
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11175)

Abstract

The UT Austin Villa team, from the University of Texas at Austin, won the 2017 RoboCup 3D Simulation League, winning all 23 games that the team played. During the course of the competition the team scored 171 goals without conceding any. Additionally, the team won the RoboCup 3D Simulation League technical challenge by winning each of a series of three league challenges: free, passing and scoring, and Gazebo running challenge. This paper describes the changes and improvements made to the team between 2016 and 2017 that allowed it to win both the main competition and each of the league technical challenges.

Notes

Acknowledgments

Thanks to members of the BahiaRT and magmaOffenburg teams for helping put together the passing and scoring challenge and the Gazebo running challenge. This work has taken place in the Learning Agents Research Group (LARG) at the Artificial Intelligence Laboratory, The University of Texas at Austin. LARG research is supported in part by NSF (IIS-1637736, IIS-1651089, IIS-1724157), Intel, Raytheon, and Lockheed Martin. Peter Stone serves on the Board of Directors of Cogitai, Inc. The terms of this arrangement have been reviewed and approved by the University of Texas at Austin in accordance with its policy on objectivity in research.

References

  1. 1.
    MacAlpine, P., et al.: UT Austin Villa 2011: a champion agent in the RoboCup 3D soccer simulation competition. In: Proceedings of 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012) (2012)Google Scholar
  2. 2.
    MacAlpine, P., Collins, N., Lopez-Mobilia, A., Stone, P.: UT Austin Villa: RoboCup 2012 3D simulation league champion. In: Chen, X., Stone, P., Sucar, L.E., van der Zant, T. (eds.) RoboCup 2012. LNCS (LNAI), vol. 7500, pp. 77–88. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-39250-4_8CrossRefGoogle Scholar
  3. 3.
    MacAlpine, P., Depinet, M., Liang, J., Stone, P.: UT Austin Villa: RoboCup 2014 3D simulation league competition and technical challenge champions. In: Bianchi, R.A.C., Akin, H.L., Ramamoorthy, S., Sugiura, K. (eds.) RoboCup 2014. LNCS (LNAI), vol. 8992, pp. 33–46. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-18615-3_3CrossRefGoogle Scholar
  4. 4.
    MacAlpine, P., Hanna, J., Liang, J., Stone, P.: UT Austin Villa: RoboCup 2015 3D simulation league competition and technical challenges champions. In: Almeida, L., Ji, J., Steinbauer, G., Luke, S. (eds.) RoboCup 2015. LNCS (LNAI), vol. 9513, pp. 118–131. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-29339-4_10CrossRefGoogle Scholar
  5. 5.
    MacAlpine, P., Stone, P.: UT Austin Villa: RoboCup 2016 3D simulation league competition and technical challenges champions. In: Behnke, S., Sheh, R., Sarıel, S., Lee, D.D. (eds.) RoboCup 2016. LNCS (LNAI), vol. 9776, pp. 515–528. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68792-6_43CrossRefGoogle Scholar
  6. 6.
    MacAlpine, P., et al.: UT Austin Villa 2011 3D simulation team report. Technical report AI11-10, The University of Texas at Austin, Departmet of Computer Science, AI Laboratory (2011)Google Scholar
  7. 7.
    Boedecker, J., Asada, M.: SimSpark-concepts and application in the RoboCup 3D soccer simulation league. In: SIMPAR 2008 Workshop on the Universe of RoboCup Simulators, pp. 174–181 (2008)Google Scholar
  8. 8.
    Xu, Y., Vatankhah, H.: SimSpark: an open source robot simulator developed by the RoboCup community. In: Behnke, S., Veloso, M., Visser, A., Xiong, R. (eds.) RoboCup 2013. LNCS (LNAI), vol. 8371, pp. 632–639. Springer, Heidelberg (2014).  https://doi.org/10.1007/978-3-662-44468-9_59CrossRefGoogle Scholar
  9. 9.
    MacAlpine, P., Price, E., Stone, P.: SCRAM: scalable collision-avoiding role assignment with minimal-makespan for formational positioning. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI 2015) (2015)Google Scholar
  10. 10.
    MacAlpine, P., Stone, P.: Prioritized role assignment for marking. In: Behnke, S., Sheh, R., Sarıel, S., Lee, D.D. (eds.) RoboCup 2016. LNCS (LNAI), vol. 9776, pp. 306–318. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68792-6_25CrossRefGoogle Scholar
  11. 11.
    MacAlpine, P., Stone, P.: Overlapping layered learning. Artif. Intell. 254, 21–43 (2018)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Hansen, N.: The CMA Evolution Strategy: A Tutorial (2009). http://www.lri.fr/~hansen/cmatutorial.pdf
  13. 13.
    Omidvar, M.N., Li, X.: A comparative study of CMA-ES on large scale global optimisation. In: Li, J. (ed.) AI 2010. LNCS (LNAI), vol. 6464, pp. 303–312. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-17432-2_31CrossRefGoogle Scholar
  14. 14.
    Dorer, K.: Learning to use toes in a humanoid robot. In: RoboCup 2017. LNAI, vol. 11175, pp. 168–179. Springer, Cham (2018)Google Scholar
  15. 15.
    Bengio, Y., Goodfellow, I.J., Courville, A.: Deep learning. Nature 521, 436–444 (2015)CrossRefGoogle Scholar
  16. 16.
    Schulman, J., Levine, S., Abbeel, P., Jordan, M., Moritz, P.: Trust region policy optimization. In: Proceedings of the 32nd International Conference on Machine Learning (ICML 2015), pp. 1889–1897 (2015)Google Scholar
  17. 17.
    Koenig, N., Howard, A.: Design and use paradigms for gazebo, an open-source multi-robot simulator. In: Intelligent Robots and Systems (IROS) (2004)Google Scholar
  18. 18.
    MacAlpine, P., Barrett, S., Urieli, D., Vu, V., Stone, P.: Design and optimization of an omnidirectional humanoid walk: a winning approach at the RoboCup 2011 3D simulation competition. In: Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2012) (2012)Google Scholar
  19. 19.
    MacAlpine, P., Stone, P.: UT Austin Villa RoboCup 3D simulation base code release. In: Behnke, S., Sheh, R., Sarıel, S., Lee, D.D. (eds.) RoboCup 2016. LNCS (LNAI), vol. 9776, pp. 135–143. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-68792-6_11CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceThe University of Texas at AustinAustinUSA

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