Advertisement

Framework for Simulating the Human Behavior for Intelligent Virtual Agents. Part II: Behavioral System

  • F. Luengo
  • A. Iglesias
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3039)

Abstract

This paper is the second in a series of two papers (both included in this volume) describing a new framework for simulating the human behavior for intelligent virtual agents. This second paper focuses on the application of Artificial Intelligence (AI) techniques to the simulation of the human cognitive process. The paper discusses some important issues involved in this process, such as the representation and identification of objects, the information acquisition and its conversion into knowledge and the learning process. The paper also describes how some standard AI techniques (expert systems, neural networks) have been applied to tackle these problems.

Keywords

Information Acquisition Impact Index Memory Area Behavioral System Request Manager 
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.

References

  1. 1.
    Castillo, E., Gutiérrez, J.M., Hadi, A.: Expert Systems and Probabilistic Network Models. Springer, New York (1997)Google Scholar
  2. 2.
    Funge, J., Tu, X., Terzopoulos, D.: Cognitive modeling: knowledge, reasoning and planning for intelligent characters. In: Proceedings of SIGGRAPH 1999, pp. 29–38. ACM, New York (1999)CrossRefGoogle Scholar
  3. 3.
    Granieri, J.P., Becket, W., Reich, B.D., Crabtree, J., Badler, N.I.: Behavioral control for real-time simulated human agents. In: Symposium on Interactive 3D Graphics, pp. 173–180. ACM, New York (1995)CrossRefGoogle Scholar
  4. 4.
    Grzeszczuk, R., Terzopoulos, D., Hinton, G.: NeuroAnimator: fast neural network emulation and control of physics-based models. In: Proceedings of SIGGRAPH 1998, pp. 9–20. ACM, New York (1998)CrossRefGoogle Scholar
  5. 5.
    Haykin, S.: Neural Networks. A Comprehensive Foundation. Macmillan Publishing, Englewood Cliffs (1994)zbMATHGoogle Scholar
  6. 6.
    Hertz, J., Krogh, A., Palmer, R.G.: Introduction to the Theory of Neural Computation. Addison Wesley, Reading (1991)Google Scholar
  7. 7.
    Monzani, J.S., Caicedo, A., Thalmann, D.: Integrating behavioral animation techniques. In: Proceedings of EUROGRAPHICS 2001, Computer Graphics Forum, vol. 20(3), pp. 309–318 (2001)Google Scholar
  8. 8.
    Ridsdale, G.: Connectionist modeling of skill dynamics. Journal of Visualization and Computer Animation 1(2), 66–72 (1990)Google Scholar
  9. 9.
    Sims, K.: Evolving virtual creatures. In: Proceedings of SIGGRAPH 1994, pp. 15–22. ACM, New York (1994)CrossRefGoogle Scholar
  10. 10.
    Van de Panne, M., Fiume, E.: Sensor-actuator networks. In: Proceedings of SIGGRAPH 1993, Computer Graphics, vol. 27, pp. 335–342 (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • F. Luengo
    • 1
    • 2
  • A. Iglesias
    • 2
  1. 1.Department of Computer ScienceUniversity of ZuliaMaracaiboVenezuela
  2. 2.Department of Applied Mathematics and Computational SciencesUniversity of CantabriaSantanderSpain

Personalised recommendations