The iCat as a Natural Interaction Partner

Playing Go Fish with a Robot
  • Koen Hindriks
  • Mark A. Neerincx
  • Mirek Vink
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7068)

Abstract

To be able to develop robots that naturally interact with humans it is important to gain a better understanding of the factors that shape this interaction. Although many aspects have already been studied in depth, few studies have been performed on the effect that socio-cognitive abilities may have on this interaction. We have developed a robot that shows intentional or proactive behavior and that can be used to conduct research on interaction that is shaped by cognitive abilities. We have used the iCat robot platform to perform experiments with children to test various hypotheses on perceived effects of socio-cognitive abilities. Two different versions were developed: a socio-cognitive iCat robot that behaves socially and takes the mood of the child into account, and an ego-reactive iCat robot that does not do so. These two robots were evaluated and compared with each other in a scenario where the robot plays the card game Go Fish with a child. Results indicate that children are more positive about the interaction with the socio-cognitive iCat than with the ego-reactive iCat.

Keywords

Facial Expression Emotion Expression Game Play Social Robot Proactive Behavior 
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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References

  1. 1.
    Fong, T., Nourbakhsh, I., Dautenhahn, K.: A survey of socially interactive robots. Robotics and Autonomous Systems 42, 143–166 (2003)CrossRefMATHGoogle Scholar
  2. 2.
    Dautenhahn, K.: Design spaces and niche spaces of believable social robots. In: Proceedings of the International Workshop on Robots and Human Interactive Communication, pp. 192–197 (2002)Google Scholar
  3. 3.
    Kozima, H., Yano, H.: In search of ontogenetic prerequisites for embodied social intelligence. In: Proceedings of the Workshop on Emergence and Development on Embodied Cognition; International Conference on Cognitive Science, pp. 30–34 (2001)Google Scholar
  4. 4.
    Kozima, H., Yano, H.: A robot that learns to communicate with human caregivers. In: Proceedings of the International Workshop on Epigenetic Robotics, pp. 47–52 (2001)Google Scholar
  5. 5.
    Breazeal, C., Scassellati, B.: How to build robots that make friends and influence people. In: Proceedings of the International Conference on Intelligent Robots and Systems (1999)Google Scholar
  6. 6.
    Heerink, M.: The influence of a robot’s social abilities on acceptance by elderly users. In: RO-MAN, Hertfordshire, pp. 521–526 (2006)Google Scholar
  7. 7.
    Looije, R., Neerincx, M.A., de Lange, V.: Children’s responses and opinion on three bots that motivate, educate and play. Journal of Physical Agents 2(2), 13–20 (2008)Google Scholar
  8. 8.
    Kessens, J.M., Neerincx, M.A., Looije, R., Kroes, M., Bloothooft, G.: Facial and vocal emotion expression of a personal computer assistant to engage, educate and motivate children. In: Third IEEE International Conference on Affective Computing and Intelligent Interaction, ACII 2009 (2009)Google Scholar
  9. 9.
    Looije, R., Neerincx, M.A., Cnossen, F.: Persuasive robotic assistant for health self-management of older adults: Design and evaluation of social behaviors. International Journal of Human-Computer Studies 68, 386–397 (2010)CrossRefGoogle Scholar
  10. 10.
    Leite, I., Martinho, C., Pereira, A., Paiva, A.: iCat: an Affective Game Buddy Based on Anticipatory Mechanisms (Short Paper). In: Proc. of 7th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2008), pp. 1229–1232 (2008)Google Scholar
  11. 11.
    Malone, T.W.: Heuristics for designing enjoyable user interfaces. lessons from computer games. In: Proceedings of the 1982 Conference on Human Factors in Computing Systems, pp. 63–68 (1982)Google Scholar
  12. 12.
  13. 13.
    Minato, T., Shimada, M., Ishiguro, H., Itakura, S.: Development of an Android Robot for Studying Human-Robot Interaction. In: Orchard, B., Yang, C., Ali, M. (eds.) IEA/AIE 2004. LNCS (LNAI), vol. 3029, pp. 424–434. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  14. 14.
    Brooks, A.G., Arkin, R.C.: Behavioral overlays for non-verbal communication expression on a humanoid robot. Autonomous Robots 22(1), 55–74 (2006)CrossRefGoogle Scholar
  15. 15.
    Hindriks, K.V.: Programming Rational Agents in Goal. In: Multi-Agent Programming, pp. 119–157. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  16. 16.
    Schlossberg, H.: Three dimensions of emotion. Psychology Review 61 (1954)Google Scholar
  17. 17.
    Rizzolatti, G., Craighero, L.: Mirror neuron: a neurological approach to empathy (2005) (manuscript)Google Scholar
  18. 18.
    Lee, C., Lesh, N., Sidner, C.L., Morency, L.P., Kapoor, A., Darrell, T.: Nodding in conversations with a robot. In: Proceedings of the Conference on Human Factors in Computing Systems, pp. 785–786 (2004)Google Scholar
  19. 19.
    Vink, M.: The iCat as a Natural Interaction Partner: Play Go Fish with a Robot. Master’s thesis, Delft University of Technology (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Koen Hindriks
    • 1
  • Mark A. Neerincx
    • 1
  • Mirek Vink
    • 1
  1. 1.Delft University of TechnologyThe Netherlands

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