Prioritized Role Assignment for Marking

  • Patrick MacAlpineEmail author
  • Peter Stone
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9776)


This paper presents a system for marking or covering players on an opposing soccer team so as to best prevent them from scoring. A basis for the marking system is the introduction of prioritized role assignment, an extension to SCRAM dynamic role assignment used by the UT Austin Villa RoboCup 3D simulation team for formational positioning. The marking system is designed to allow for decentralized coordination among physically realistic simulated humanoid soccer playing robots in the partially observable, non-deterministic, noisy, dynamic, and limited communication setting of the RoboCup 3D simulation league simulator. Although it is discussed in the context of the RoboCup 3D simulation environment, the marking system is not domain specific and can readily be employed in other RoboCup leagues as prioritized role assignment generalizes well to many realistic and real-world multiagent systems.



This work has taken place in the Learning Agents Research Group (LARG) at UT Austin. LARG research is supported in part by NSF (CNS-1330072, CNS-1305287), ONR (21C184-01), and AFOSR (FA9550-14-1-0087). Peter Stone serves on the Board of Directors of, Cogitai, Inc. The terms of this arrangement have been reviewed and approved by UT Austin in accordance with its policy on objectivity in research.


  1. 1.
    Boedecker, J., Asada, M.: Simspark-concepts and application in the RoboCup 3D soccer simulation league. In: Autonomous Robots, pp. 174–181 (2008)Google Scholar
  2. 2.
    Chen, W., Chen, T.: Multi-robot dynamic role assignment based on path cost. In: 2011 Chinese Control and Decision Conference (CCDC), pp. 3721–3724, May 2011Google Scholar
  3. 3.
    Habibi, J., Younesy, H., Heydarnoori, A.: Using the opponent pass modeling method to improve defending ability of a (Robo)Soccer simulation team. In: Polani, D., Browning, B., Bonarini, A., Yoshida, K. (eds.) RoboCup 2003. LNCS, vol. 3020, pp. 543–550. Springer, Heidelberg (2004). Scholar
  4. 4.
    Kuhn, H.W.: The Hungarian method for the assignment problem. Naval Res. Logistics Q. 2(1–2), 83–97 (1955)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Kyrylov, V., Hou, E.: Pareto-optimal collaborative defensive player positioning in simulated soccer. In: Baltes, J., Lagoudakis, M.G., Naruse, T., Ghidary, S.S. (eds.) RoboCup 2009. LNCS (LNAI), vol. 5949, pp. 179–191. Springer, Heidelberg (2010). Scholar
  6. 6.
    Lau, N., Lopes, L., Corrente, G., Filipe, N.: Multi-robot team coordination through roles, positionings and coordinated procedures. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009), pp. 5841–5848, October 2009Google Scholar
  7. 7.
    Li, C., Xiong, R., Ren, Z., Tang, W., Zhao, Y.: ZJUNlict: RoboCup 2014 small size league champion. In: Bianchi, R.A.C., Akin, H.L., Ramamoorthy, S., Sugiura, K. (eds.) RoboCup 2014. LNCS (LNAI), vol. 8992, pp. 47–59. Springer, Cham (2015). Scholar
  8. 8.
    Li, X., Chen, X.: Fuzzy inference based forecasting in soccer simulation 2D, the RoboCup 2015 soccer simulation 2D league champion team. In: Almeida, L., Ji, J., Steinbauer, G., Luke, S. (eds.) RoboCup 2015. LNCS (LNAI), vol. 9513, pp. 144–152. Springer, Cham (2015). Scholar
  9. 9.
    MacAlpine, P., Barrera, F., Stone, P.: Positioning to win: a dynamic role assignment and formation positioning system. In: Chen, X., Stone, P., Sucar, L.E., Zant, T. (eds.) RoboCup 2012. LNCS (LNAI), vol. 7500, pp. 190–201. Springer, Heidelberg (2013). Scholar
  10. 10.
    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). Scholar
  11. 11.
    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). Scholar
  12. 12.
    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-15), January 2015Google Scholar
  13. 13.
    Mendoza, J.P., Biswas, J., Zhu, D., Wang, R., Cooksey, P., Klee, S., Veloso, M.: CMDragons 2015: coordinated offense and defense of the SSL champions. In: Almeida, L., Ji, J., Steinbauer, G., Luke, S. (eds.) RoboCup 2015. LNCS (LNAI), vol. 9513, pp. 106–117. Springer, Cham (2015). Scholar
  14. 14.
    Reis, L.P., Lau, N., Oliveira, E.C.: Situation based strategic positioning for coordinating a team of homogeneous agents. BRSDMAS 2000. LNCS, vol. 2103, pp. 175–197. Springer, Heidelberg (2001). Scholar
  15. 15.
    Stone, P., Veloso, M.: Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork. Artif. Intell. 110(2), 241–273 (1999)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

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

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