Controlling Three Agents in a Quarrel: Lessons Learnt

  • Cyril Brom
  • Petr Babor
  • Markéta Popelová
  • Michal Bída
  • Jakub Tomek
  • Jakub Gemrot
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7660)


Steering behaviours can be used to position 3D embodied agents in small groups engaged in relatively simple social interactions such as in group conversation or walking while talking. Less is known about scaling these mechanisms for situations with complex dynamics requiring agents to perform actions beyond walking, turning, talking and gesturing. Here, we present a model for controlling three agents in an example of such a situation: a vigorous quarrel. The model combines a general steering behaviour for keeping the three agents in a triangular formation with a probabilistic two-level hierarchical state machine (hFSM) for unfolding the quarrel by means of changing parameters of the steering behaviour and issuing actions to the agents. The model has been implemented using UnrealEngine2Runtime on the example of a boy dating two girls at the same time who do not know about each other. The user can influence the course of the quarrel by changing attitudes among the agents. To create a list of the agents’ actions and the hFSM, we video-taped about 40 episodes in which three actors improvised on the topic of the quarrel, and we manually annotated the videos. The evaluation with 67 human participants indicates that the model produces outcomes comprehensible and believable even for persons with limited previous experience with 3D graphics. On a more general level, this paper suggests that augmenting steering behaviours by a non-trivial higher-level controller is a feasible approach to modelling behaviour of 3D agents interacting in small groups in a complex way and presents a possible workflow for developing scenes featuring such agents.


Target Location Virtual Agent Border Point Crowd Simulation Control Video 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bída, M., Brom, C., Popelová, M., Kadlec, R.: StoryFactory – A Tool for Scripting Machinimas in Unreal Engine 2 and UDK. In: Si, M., Thue, D., André, E., Lester, J.C., Tanenbaum, J., Zammitto, V. (eds.) ICIDS 2011. LNCS, vol. 7069, pp. 334–337. Springer, Heidelberg (2011)Google Scholar
  2. 2.
    Damian, I., Endrass, B., Huber, P., Bee, N., André, E.: Individualized Agent Interactions. In: Allbeck, J.M., Faloutsos, P. (eds.) MIG 2011. LNCS, vol. 7060, pp. 15–26. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  3. 3.
    Gemrot, J., Kadlec, R., Bída, M., Burkert, O., Píbil, R., Havlíček, J., Zemčák, L., Šimlovič, J., Vansa, R., Štolba, M., Plch, T., Brom, C.: Pogamut 3 Can Assist Developers in Building AI (Not Only) for Their Videogame Agents. In: Dignum, F., Bradshaw, J., Silverman, B., van Doesburg, W. (eds.) Agents for Games and Simulations. LNCS, vol. 5920, pp. 1–15. Springer, Heidelberg (2009), (July 6, 2012)CrossRefGoogle Scholar
  4. 4.
    Jan, D., Traum, D.R.: Dynamic movement and positioning of embodied agents in multiparty conversations. In: Proceedings of the Workshop on Embodied Language Processing, pp. 59–66 (2007)Google Scholar
  5. 5.
    Karamouzas, I., Overmars, M.: Simulating the Local Behaviour of Small Pedestrian Groups. In: Proc. of the 17th VRST, pp. 183–190 (2011)Google Scholar
  6. 6.
    Kendon, A.: Conducting Interaction: Patterns of Behavior in Focused Encounters. Cambridge University Press (1990)Google Scholar
  7. 7.
    Mayer, R.E.: Multimedia learning. Cambridge University Press, New York (2001)CrossRefGoogle Scholar
  8. 8.
    Mateas, M.: Interactive Drama, Art and Artificial Intelligence. PhD thesis. Department of Computer Science, Carnegie Mellon University (2002)Google Scholar
  9. 9.
    Narain, R., Golas, A., Curtis, S., Lin, M.C.: Aggregate dynamics for dense crowd simulation. In: ACM SIGGRAPH Asia 2009 Papers, pp. 122:1–122:8 (2009)Google Scholar
  10. 10.
    O’Neill, B., Piplica, A., Fuller, D., Magerko, B.: A Knowledge-Based Framework for the Collaborative Improvisation of Scene Introductions. In: Si, M., Thue, D., André, E., Lester, J.C., Tanenbaum, J., Zammitto, V. (eds.) ICIDS 2011. LNCS, vol. 7069, pp. 85–96. Springer, Heidelberg (2011)Google Scholar
  11. 11.
    Orkin, J., Roy, D.: Automatic learning and generation of social behavior from collective human gameplay. In: Proceedings of the 8th International Conference on Autonomous Agents and Multiagent Systems, vol. 1, pp. 385–392 (2009)Google Scholar
  12. 12.
    Pedica, C., Vilhjálmsson, H.: Spontaneous avatar behavior for human territoriality. Applied Artificial Intelligence 24, 575–593 (2010)CrossRefGoogle Scholar
  13. 13.
    Peinado, F., Cavazza, M., Pizzi, D.: Revisiting Character-Based Affective Storytelling under a Narrative BDI Framework. In: Spierling, U., Szilas, N. (eds.) ICIDS 2008. LNCS, vol. 5334, pp. 83–88. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  14. 14.
    Popelová, M., Bída, M., Brom, C., Gemrot, J., Tomek, J.: When a Couple Goes Together: Walk along Steering. In: Allbeck, J.M., Faloutsos, P. (eds.) MIG 2011. LNCS, vol. 7060, pp. 278–289. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  15. 15.
    Porteous, J., Cavazza, M., Charles, F.: Applying Planning to Interactive Storytelling: Narrative Control using State Constraints. ACM TIST 1(2), 1–21 (2010)Google Scholar
  16. 16.
    Reynolds, C.: Steering behaviors for autonomous characters. In: GDC, pp. 763–782 (1999)Google Scholar
  17. 17.
    Ricks, B.C., Egbert, P.K.: More realistic, flexible, and expressive social crowds using transactional analysis. The Visual Computer 28(6-8), 889–898 (2012)CrossRefGoogle Scholar
  18. 18.
    Thalmann, D.: Crowd Simulation. In: Wiley Encyclopedia of Computer Science and Engineering. John Wiley & Sons, Inc. (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cyril Brom
    • 1
  • Petr Babor
    • 1
  • Markéta Popelová
    • 1
  • Michal Bída
    • 1
  • Jakub Tomek
    • 1
  • Jakub Gemrot
    • 1
  1. 1.Faculty of Mathematics and PhysicsCharles University in PraguePragueCzech Republic

Personalised recommendations