Teachable Characters: User Studies, Design Principles, and Learning Performance

  • Andrea L. Thomaz
  • Cynthia Breazeal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4133)


Teachable characters can enhance entertainment technology by providing new interactions, becoming more competent at game play, and simply being fun to teach. It is important to understand how human players try to teach virtual agents in order to design agents that learn effectively from this instruction. We present results of a user study where people teach a virtual agent a novel task within a reinforcement-based learning framework. Analysis yields lessons of how human players approach the task of teaching a virtual agent: 1) they want to direct the agent’s attention; 2) they communicate both instrumental and motivational intentions; 3) they tailor their instruction to their understanding of the agent; and 4) they use negative communication as both feedback and as a suggestion for the next action. Based on these findings we modify the agent’s learning algorithm and show improvements to the learning interaction in follow-up studies. This work informs the design of real-time learning agents that better match human teaching behavior to learn more effectively and be more enjoyable to teach.


Teachable Character Virtual Agent Learning Agent Feedback Message Human Player 
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.


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  1. 1.
    Evans, R.: Varieties of learning. In: Rabin, S. (ed.) AI Game Programming Wisdom, pp. 567–578. Charles River Media, Hingham (2002)Google Scholar
  2. 2.
    Stanley, K.O., Bryant, B.D., Miikkulainen, R.: Evolving neural network agents in the nero video game. In: Proceedings of IEEE 2005 Symposium on Computational Intelligence and Games (CIG 2005) (2005)Google Scholar
  3. 3.
    Stern, A., Frank, A., Resner, B.: Virtual petz (video session): a hybrid approach to creating autonomous, lifelike dogz and catz. In: AGENTS 1998: Proceedings of the second international conference on Autonomous agents, pp. 334–335. ACM Press, New York (1998)CrossRefGoogle Scholar
  4. 4.
    Blumberg, B., Downie, M., Ivanov, Y., Berlin, M., Johnson, M., Tomlinson, B.: Integrated learning for interactive synthetic characters. In: Proceedings of the ACM SIGGRAPH (2002)Google Scholar
  5. 5.
    Kaplan, F., Oudeyer, P.Y., Kubinyi, E., Miklosi, A.: Robotic clicker training. Robotics and Autonomous Systems 38(3-4), 197–206 (2002)CrossRefGoogle Scholar
  6. 6.
    Isbell, C., Shelton, C., Kearns, M., Singh, S., Stone, P.: Cobot: A social reinforcement learning agent. In: 5th Intern. Conf. on Autonomous Agents (2001)Google Scholar
  7. 7.
    Kuhlmann, G., Stone, P., Mooney, R.J., Shavlik, J.W.: Guiding a reinforcement learner with natural language advice: Initial results in robocup soccer. In: Proceedings of the AAAI 2004 Workshop on Supervisory Control of Learning and Adaptive Systems, San Jose, CA (2004)Google Scholar
  8. 8.
    Watkins, C., Dayan, P.: Q-learning. Machine Learning 8(3), 279–292 (1992)zbMATHGoogle Scholar
  9. 9.
    Kaelbling, L.P., Littman, M.L., Moore, A.P.: Reinforcement learning: A survey. Journal of Artificial Intelligence Research 4, 237–285 (1996)Google Scholar
  10. 10.
    Breazeal, C., Brooks, A., Gray, J., Hoffman, G., Lieberman, J., Lee, H., Lockerd, A., Mulanda, D.: Tutelage and collaboration for humanoid robots. International Journal of Humanoid Robotics 1(2) (2004)Google Scholar
  11. 11.
    Thomas, F., Johnson, O.: Disney Animation: The Illusion of Life. Abbeville Press, New York (1981)Google Scholar
  12. 12.
    Bates, J.: The role of emotion in believable agents. Communications of the ACM 37(7), 122–125 (1997)CrossRefGoogle Scholar
  13. 13.
    Blumberg, B.: Old tricks, new dogs: ethology and interactive creatures. PhD thesis, Massachusetts Institute of Technology (1997)Google Scholar
  14. 14.
    Tomlinson, B., Blumberg, B.: Social synthetic characters. Computer Graphics 26(2) (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Andrea L. Thomaz
    • 1
  • Cynthia Breazeal
    • 1
  1. 1.MIT Media LabCambridgeUSA

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