Advertisement

Autonomous Robots

, Volume 12, Issue 1, pp 13–24 | Cite as

Theory of Mind for a Humanoid Robot

  • Brian Scassellati
Article

Abstract

If we are to build human-like robots that can interact naturally with people, our robots must know not only about the properties of objects but also the properties of animate agents in the world. One of the fundamental social skills for humans is the attribution of beliefs, goals, and desires to other people. This set of skills has often been called a “theory of mind.” This paper presents the theories of Leslie (1994) and Baron-Cohen (1995) on the development of theory of mind in human children and discusses the potential application of both of these theories to building robots with similar capabilities. Initial implementation details and basic skills (such as finding faces and eyes and distinguishing animate from inanimate stimuli) are introduced. I further speculate on the usefulness of a robotic implementation in evaluating and comparing these two models.

humanoid robots visual perception social interaction 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Adams, B., Breazeal, C., Brooks, R., and Scassellati, B. 2000. Humanoid robotics: A new kind of tool. IEEE Intelligent Systems, 15(4):25–31.Google Scholar
  2. Baron-Cohen, S. 1995. Mindblindness, MIT Press: Cambridge, MA.Google Scholar
  3. Breazeal, C., Edsinger, A., Fitzpatrick, P., Scassellati, B., and Varchavskaia, P. 2000. Social constraints on animate vision. IEEE Intelligent Systems, 15(4):32–37.Google Scholar
  4. Breazeal, C. and Scassellati, B. 1999. A context-dependent attention system for a social robot. In 1999 International Joint Conference on Artificial Intelligence.Google Scholar
  5. Breazeal, C. and Scassellati, B. 2002. Infant-like social interactions between a robot and a human caretaker. Adaptive Behavior (to appear).Google Scholar
  6. Brooks, R.A., Breazeal (Ferrell), C., Irie, R., Kemp, C.C., Marjanovi?, M., Scassellati, B., and Williamson, M.M. 1998. Alternative essences of intelligence. In Proceedings of the American Association of Artificial Intelligence (AAAI-98).Google Scholar
  7. Brooks, R.A., Breazeal, C., Marjanovic, M., Scassellati, B., and Williamson, M.M. 1999. The Cog project: Building a humanoid robot. In Computation for Metaphors, Analogy and Agents, C.L. Nehaniv (Ed.), Springer Lecture Notes in Artificial Intelligence, Vol. 1562, Springer-Verlag: Berlin.Google Scholar
  8. Butterworth, G. 1991. The ontogeny and phylogeny of joint visual attention. In Natural Theories of Mind, A. Whiten (Ed.), Blackwell: Oxford, 1988.Google Scholar
  9. Byrne, R. and Whiten, A. (Eds.). Machiavellian Intelligence: Social Expertise and the Evolution of Intellect in Monkeys, Apes, and Humans. Oxford University Press: Oxford.Google Scholar
  10. Carey, S. 1999. Sources of conceptual change. In Conceptual Development: Piaget's Legacy, E.K. Scholnick, K. Nelson, S.A. Gelman, and P.H. Miller (Eds.), Lawrence Erlbaum Associates: New York, pp. 293–326.Google Scholar
  11. Cheney, D.L. and Seyfarth, R.M. 1990. How Monkeys See theWorld, University of Chicago Press: Chicago, IL.Google Scholar
  12. Cheney, D.L. and Seyfarth, R.M. 1991. Reading minds or reading behavior? Tests for a theory of mind in monkeys. In Natural Theories of Mind, A. Whiten (Ed.), Blackwell: Oxford.Google Scholar
  13. Cohen, L.B. and Amsel, G. 1998. Precursors to infants' perception of the causality of a simple event. Infant Behavior and Develoment, 21(4):713–732.Google Scholar
  14. Cox, I.J. and Hingorani, S.L. 1996. An efficient implementation of Reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 18(2):138–150.Google Scholar
  15. Dennett, D.C. 1987. The Intentional Stance, MIT Press: Cambridge, MA.Google Scholar
  16. Fagan, J.F. 1976. Infants' recognition of invariant features of faces. Child Development, 47:627–638.Google Scholar
  17. Fodor, J. 1992. A theory of the child's theory of mind. Cognition, 44:283–296.Google Scholar
  18. Frith, C.D. and Frith, U. 1999. Interacting minds—Abiological basis. Science, 286:1692–1695.Google Scholar
  19. Gelman, R. 1990. First principles organize attention to and learning about relevant data: Number and the animate-inanimate distinction as examples. Cognitive Science, 14:79–106.Google Scholar
  20. Hauser, M. and Carey, S. 1998. Building a cognitive creature from a set of primitives: Evolutionary and developmental insights. In The Evolution of Mind, D.D. Cummins and C. Allen (Eds.), Oxford University Press: New York.Google Scholar
  21. Hauser, M.D. 1996. Evolution of Communication, MIT Press: Cambridge, MA.Google Scholar
  22. Itti, L., Koch, C., and Niebur, E. 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 20(11):1254–1259.Google Scholar
  23. Jain, R., Kasturi, R., and Schunck, B.G. 1995. Machine Vision, McGraw-Hill: New York.Google Scholar
  24. Karmiloff-Smith, A., Klima, E., Bellugi, U., Grant, J., and Baron-Cohen, S. 1995. Is there a social module? Language, face processing, and theory of mind in individuals with Williams Syndrome. Journal of Cognitive Neuroscience, 7(2):196–208.Google Scholar
  25. Leslie, A.M. 1982. The perception of causality in infants. Perception, 11:173–186.Google Scholar
  26. Leslie, A.M. 1984. Spatiotemporal continuity and the perception of causality in infants. Perception, 13:287–305.Google Scholar
  27. Leslie, A.M. 1994. ToMM, ToBY, and Agency: Core architecture and domain specificity. In Mapping the Mind: Domain Specificity in Cognition and Culture, L.A. Hirschfeld and S.A. Gelman (Eds.), Cambridge University Press: Cambridge, pp. 119–148.Google Scholar
  28. Michotte, A. 1962. The Perception of Causality, Methuen: Andover, MA.Google Scholar
  29. Mundy, P. and Sigman, M. 1989. The theoretical implications of joint attention deficits in autism. Development and Psychopathology, 1:173–183.Google Scholar
  30. Nothdurft, H.C. 1993. The role of features in preattentive vision: Comparison of orientation, motion and color cues. Vision Research, 33:1937–1958.Google Scholar
  31. Perner, J. and Lang, B. 1999. Development of theory of mind and executive control. Trends in Cognitive Sciences, 3(9):337–344.Google Scholar
  32. Povinelli, D.J. and Preuss, T.M. 1995. Theory of mind: Evolutionary history of a cognitive specialization. Trends in Neuroscience, 18(9):418–424.Google Scholar
  33. Premack, D. 1988. "Does the chimpanzee have a theory of mind?" revisited. In Machiavellian Intelligence: Social Expertise and the Evolution of Intellect in Monkeys, Apes, and Humans, R. Byrne and A. Whiten (Eds.), Oxford University Press: Oxford.Google Scholar
  34. Reid, D.B. 1979. An algorithm for tracking multiple targets. IEEE Transactions on Automated Control, AC-24(6):843–854.Google Scholar
  35. Scassellati, B. 1998. Finding eyes and faces with a foveated vision system. In Proceedings of the American Association of Artificial Intelligence (AAAI-98).Google Scholar
  36. Sinha, P. 1996. Perceiving and recognizing three-dimensional forms. Ph.D. Thesis, Massachusetts Institute of Technology.Google Scholar
  37. Wimmer, H. and Perner, J. 1983. Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children's understanding of deception. Cognition, 13:103–128.Google Scholar
  38. Wolfe, J.M. Guided search 2.0: A revised model of visual search. Psychonomic Bulletin & Review, 1(2):202–238.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Brian Scassellati
    • 1
  1. 1.Department of Computer ScienceYale UniversityNew HavenUSA

Personalised recommendations