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Goals are not implied by actions, but inferred from actions and contexts

Published online by Cambridge University Press:  08 April 2008

Iris van Rooij
Affiliation:
Nijmegen Institute for Cognition and Information, Radboud University Nijmegen, 6500 HE Nijmegen, The Netherlands. i.vanrooij@nici.ru.nlw.haselager@nici.ru.nlh.bekkering@nici.ru.nl
Willem Haselager
Affiliation:
Nijmegen Institute for Cognition and Information, Radboud University Nijmegen, 6500 HE Nijmegen, The Netherlands. i.vanrooij@nici.ru.nlw.haselager@nici.ru.nlh.bekkering@nici.ru.nl
Harold Bekkering
Affiliation:
Nijmegen Institute for Cognition and Information, Radboud University Nijmegen, 6500 HE Nijmegen, The Netherlands. i.vanrooij@nici.ru.nlw.haselager@nici.ru.nlh.bekkering@nici.ru.nl

Abstract

People cannot understand intentions behind observed actions by direct simulation, because goal inference is highly context dependent. Context dependency is a major source of computational intractability in traditional information-processing models. An embodied embedded view of cognition may be able to overcome this problem, but then the problem needs recognition and explication within the context of the new, layered cognitive architecture.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2008

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References

Bylander, T., Allemang, D., Tanner, M. C. & Josephson, J. R. (1991) The computational complexity of abduction. Artificial Intelligence 49:2560.CrossRefGoogle Scholar
Cooper, G. F. (1990) The computational complexity of probabilistic inference using Bayesian belief networks. Artificial Intelligence 42(2–3):393405.CrossRefGoogle Scholar
Cuijpers, R. H., van Schie, H. T., Koppen, M., Erlhagen, W. & Bekkering, H. (2006) Goals and means in action observation: A computational approach. Neural Networks 19:311–22.CrossRefGoogle ScholarPubMed
de Lange, F. P., Spronk, M., Willems, R. M., Toni, I. & Bekkering, H. (submitted) Complementary systems for understanding action intentions.Google Scholar
Ford, K. M. & Pylyshyn, Z. W., eds. (1996) The robot's dilemma revisited: The frame problem in artificial intelligence. Ablex.Google Scholar
Gergely, G., Bekkering, H. & Király, I. (2002) Rational imitation in preverbal infants. Nature 415:755.CrossRefGoogle ScholarPubMed
Haselager, W. F. G. (1997) Cognitive science and folk psychology: The right frame of mind. Sage.Google Scholar
Newman-Norlund, R. D., van Schie, H. T., van Zuijlen, A. M. J., & Bekkering, H. (2007) The mirror neuron system is more active during complementary compared with imitative action. Nature Neuroscience 10(7):817–18.CrossRefGoogle ScholarPubMed
Pylyshyn, Z. W., ed. (1987) The robot's dilemma: The frame problem in artificial intelligence. Ablex.Google Scholar
Thagard, P. (2000) Coherence in thought and action. MIT Press.CrossRefGoogle Scholar
van Dijk, J., Kerkhofs, R., van Rooij, I. & Haselager, P. (in press) Can there be such a thing as embodied embedded cognitive neuroscience? Theory and Psychology.Google Scholar
van Rooij, I., Bongers, R. M. & Haselager, W. F. G. (2002) A non-representational approach to imagined action. Cognitive Science 26(3):345–75.Google Scholar
van Rooij, I., & Wareham, T. (in press) Parameterized complexity in cognitive modeling: Foundations, applications and opportunities. Computer Journal.Google Scholar