Simulation Level of Detail for Virtual Humans

  • Cyril Brom
  • Ondřej Šerý
  • Tomáš Poch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4722)


Graphical level of detail (LOD) is a set of techniques for coping with the issue of limited computational resources by reducing the graphical detail of the scene far from the observer. Simulation LOD reduces quality of the simulation at the places unseen. Contrary to graphical LOD, simulation LOD has been almost unstudied. As a part of our on-going effort on a large virtual-storytelling game populated by tens of complex virtual humans, we have developed and implemented a set of simulation LOD algorithms for simplifying virtual space and behaviour of virtual humans. The main feature of our technique is that it allows for several degrees of detail, i.e. for gradual varying of simulation quality. In this paper, we summarise the main lessons learned, introduce the prototype implementation called IVE and discuss the possibility of scaling our technique to other applications featuring virtual humans.


Atomic Action Simulation Level Virtual Human Full Simulation View Level 
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.
    Adzima, J.: AI Madness: Using AI to Bring Open-City Racing to Life. In: Gamasutra Online (January 24, 2001) [6.3.2007] (2001)Google Scholar
  2. 2.
    Alelo Inc.: Tactical Iraqi: a learning program for Iraqi Arabic [18.11.2006] (2005),
  3. 3.
    Aylett, R.S., Louchart, S., Dias, J., Paiva, A., Vala, M.: FearNot! – An Experiment in Emergent Narrative. In: Panayiotopoulos, T., Gratch, J., Aylett, R., Ballin, D., Olivier, P., Rist, T. (eds.) IVA 2005. LNCS (LNAI), vol. 3661, pp. 305–316. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Bída, M.: Emotion bots in Unreal Tournament (in Czech) Bachelor thesis. Faculty of Mathematics-Physics. Charles University in Prague (2006)Google Scholar
  5. 5.
    Brockington, M.: Level-Of-Detail AI for a Large Role-Playing Game. In: AI Game Programming Wisdom I, pp. 419–425. Charles River Media, Inc., Hingham, Mas (2002)Google Scholar
  6. 6.
    Brom, C.: Action Selection for Virtual Humans in Large Environments (in Czech) PhD thesis. Faculty of Mathematics-Physics. Charles University in Prague (2007)Google Scholar
  7. 7.
    Brom, C., Abonyi, A.: Petri-Nets for Game Plot. In: Proceedings of AISB Artificial Intelligence and Simulation Behaviour Convention, Bristol, vol. 3, pp. 6–13 (2006)Google Scholar
  8. 8.
    Brom, C., Lukavský, J., Šerý, O., Poch, T., Šafrata, P.: Affordances and level-of-detail AI for virtual humans. In: Proceedings of Game Set and Match 2, The Netherlands, Delft (2006) (6-3-2007),
  9. 9.
    Bryson, J.J.: Intelligence by Design: Principles of Modularity and Coordination for Engineering Complex Adaptive Agents. PhD thesis, Mas. Institute of Technology (2001)Google Scholar
  10. 10.
    Champandard, A.J.: AI Game Development: Synthetic Creatures with learning and Reactive Behaviors. New Riders, USA (2003)Google Scholar
  11. 11.
    Chenney, S.: Simulation Level-Of-Detail. In: GDC (2001) (6-3-2007),
  12. 12.
    Gilbert, N., den Besten, M., et al.: Emerging Artificial Societies Through Learning. The Journal of Artificial Societies and Social Simulation, JASSS, 9(2) (2006)Google Scholar
  13. 13.
    Grinke, S.: Minimizing Agent Processing in “Conflict: Desert Strom”. In: AI Game Programming Wisdom II, pp. 373–378. Charles River Media, Inc., Hingham, Mas (2004)Google Scholar
  14. 14.
    Jan, D., Traum, D.R.: Dialog Simulation for Background Characters. In: Panayiotopoulos, T., Gratch, J., Aylett, R., Ballin, D., Olivier, P., Rist, T. (eds.) IVA 2005. LNCS (LNAI), vol. 3661, Springer, Heidelberg (2005)CrossRefGoogle Scholar
  15. 15.
    McNamee, B., Dobbyn, S., Cunningham, P., O´Sullivan, C.: Men Behaving Appropriately: Integrating the Role Passing Technique into the ALOHA system. In: Proceedings of the Animating Expressive Characters for Social Interactions (2002)Google Scholar
  16. 16.
    de Sevin, E., Thalmann, D.: A motivational Model of Action Selection for Virtual Humans. In: Computer Graphics International, IEEE Computer Society Press, New York (2005)Google Scholar
  17. 17.
    Shao, W., Terzopoulos, D.: Environmental modeling for autonomous virtual pedestrians. In: Proceedings of 2005 SAE Symposium on Digital Human Modeling for Design and Engineering, Iowa City, Iowa (June 2005)Google Scholar
  18. 18.
    Šerý, O., Poch, T., Šafrata, P., Brom, C.: Level-Of-Detail in Behaviour of Virtual Humans. In: Wiedermann, J., Tel, G., Pokorný, J., Bieliková, M., Štuller, J. (eds.) SOFSEM 2006. LNCS, vol. 3831, pp. 565–574. Springer, Heidelberg (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Cyril Brom
    • 1
  • Ondřej Šerý
    • 1
  • Tomáš Poch
    • 1
  1. 1.Charles University in Prague, Faculty of Mathematics and Physics, Malostranské nám. 2/25, PragueCzech Republic

Personalised recommendations