Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-16T04:21:11.338Z Has data issue: false hasContentIssue false

9 - The dynamic emergence of categories through imitation

Published online by Cambridge University Press:  10 December 2009

Tony Belpaeme
Affiliation:
School of Computing, Communications and Electronics, University of Plymouth, UK
Bart de Boer
Affiliation:
Rijksuniversiteit Groningen, Kunstmatige Intelligentie, The Netherlands
Bart Jansen
Affiliation:
Artificial Intelligence Lab, Vrije Universiteit Brussel (VUB), Belgiam
Chrystopher L. Nehaniv
Affiliation:
University of Hertfordshire
Kerstin Dautenhahn
Affiliation:
University of Hertfordshire
Get access

Summary

Introduction

Imitation is a powerful mechanism to culturally propagate and maintain knowledge and abilities. Not only humans rely heavily on imitation and social learning in general, but also animals such as dolphins, some bird species and some primates rely on imitation to acquire gestures and articulations (see e.g. Dautenhahn and Nehaniv, 2002b; Whiten and Ham, 1992). Studies on social learning in cognitive science have concentrated on mimicry, joint attention, the relationship between imitator and imitated, theory of mind, intentionality, speech (Kuhl and Meltzoff, 1996) and learning affordances of objects and tools (Tomasello, 1999). All these issues have been considered by artificial intelligence in constructing artefacts that learn from imitation, either in simulation (e.g. Alissandrakis et al., 2001) or on robotic platforms (e.g. Kuniyoshi et al., 1994; Gaussier et al., 1998; Billard and Hayes, 1997; Schaal, 1999). In this chapter however we wish to pay attention to the role of the social medium in which imitation takes place. Often, imitation is considered to take place only between two agents: one acts as teacher and the other as student. The teacher is in possession of a full repertoire of gestures, actions or articulations, which the student has to acquire through imitation learning. This is of course a valid approach when one is interested in the paradigm of imitation to program artefacts by demonstration (Bakker and Kuniyoshi, 1996).

Type
Chapter
Information
Imitation and Social Learning in Robots, Humans and Animals
Behavioural, Social and Communicative Dimensions
, pp. 179 - 194
Publisher: Cambridge University Press
Print publication year: 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alissandrakis, A., Nehaniv, C. L. and Dautenhahn, K. (2001). Through the looking-glass with ALICE – trying to imitate using correspondences. In Balkenius, C., Zlatev, J., Kozima, H., Dautenhahn, K. and Breazeal, C. (eds.), Proceedings of the First International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, Lund University Cognitive Studies. September 17–18, 2001, Lund, Sweden, Vol. 85.Google Scholar
Alissandrakis, A., Nehaniv, C. L. and Dautenhahn, K. (2003). Synchrony and perception in robotic imitation across embodiments. In IEEE International Symposium on computational intelligence in robotics and automation (CIRA '03), 923–30.
Alissandrakis, A., Nehaniv, C. L. and Dautenhahn, K. (2004). Towards robot cultures? Learning to imitate in a robotic arm test-bed with dissimilar embodied agents. Interaction studies: Social behaviour and communication in biological and artificial systems, 5, 3–44.CrossRefGoogle Scholar
Bakker, P. and Kuniyoshi, Y. (1996). Robot see, robot do: an overview of robot imitation. In Proceedings of the AISB Workshop on Learning in Robots and Animals, Brighton, UK, April 1996, 3–11.Google Scholar
Billard, A. and Hayes, G. (1997). Transmitting communication skills through imitation in autonomous robots. In Birk, A. and Demiris, Y. (eds.), Proceedings of EWLR97, Sixth European Workshop on Learning Robots. Brighton, UK, July 1997.Google Scholar
Billard, A. and Matarić, M. J. (2001). Learning human arm movements by imitation: evaluation of a biologically inspired connectionist architecture. Robotics and Autonomous Systems, 37(2–3), 145–60.CrossRefGoogle Scholar
Dautenhahn, K. and Nehaniv, C. L. (2002a). The agent-based perspective on imitation. In Dautenhahn, K. and Nehaniv, C. L. (eds.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press, 1–40.Google Scholar
Dautenhahn, K. and Nehaniv, C. L. (eds.) (2002b). Imitation in Animals and Artifacts. Cambridge, MA: MIT Press.Google Scholar
Boer, B. (2000). Self-organisation in vowel systems. Journal of Phonetics, 28(4), 441–65.CrossRefGoogle Scholar
Boer, B. (2001). The Origins of Vowel Systems. Oxford, UK: Oxford University Press.Google Scholar
Gaussier, P., Moga, S., Quoy, M. and Banquet, J.-P. (1998). From perception-action loops to imitation processes: a bottom-up approach of learning by imitation. Applied Artificial Intelligence, 12(7–8), 701–27.CrossRefGoogle Scholar
Jansen, B. (2003). An imitation game for emerging action categories. In Banzhaf, W., Christaller, T., Dittrich, P., Kim, J. T. and Ziegler, J. (eds.), Advances in Artificial Life, 7th European Conference on Artificial Life (ECAL 2003), Dortmund, Germany, Vol. 2801 of Lecture Notes in Computer Science. Berlin: Springer, 800–9.Google Scholar
Jansen, B., de Boer, B. and Belpaeme, T. (2004a). You did it on purpose! Towards intentional embodied agents. In Iida, F., Pfeifer, R., Steels, L. and Kuniyoshi, Y. (eds.), Embodied Artificial Intelligence. Berlin: Springer, 271–7.CrossRefGoogle Scholar
Jansen, B., De Vylder, B., Belpaeme, T. and de Boer, B. (2003). Emerging shared action categories in robotic agents through imitation. In Dautenhahn, K. and Nehaniv, C. L. (eds.), Second International Symposium on Imitation in Animals and Artifacts 2003. The Society for the Study of Artificial Intelligence and the Simulation of Behavior, 145–52.Google Scholar
Jansen, B., ten Thij, T., Belpaeme, T., De Vylder, B. and de Boer, B. (2004b). Imitation in embodied agents results in self-organization of behavior. In Schaal, S., Ijspeert, A. J., Billard, A. and Vijayakumar, S. (eds.), From Animals to Animats: Proceedings of the 8th Conference on the Simulation of Adaptive Behavior. Cambridge, MA: The MIT Press.Google Scholar
Kuhl, P. K. and Meltzoff, A. N. (1996). Infant vocalizations in response to speech: vocal imitation and developmental change. The Journal of the Acoustical Society of America, 100(4), 2425–38.CrossRefGoogle ScholarPubMed
Kuniyoshi, Y., Inaba, M. and Inoue, H. (1994). Learning by watching: extracting reusable task knowledge from visual observation of human performance. IEEE Transactions on Robotics and Automation, 10(6), 799–822.CrossRefGoogle Scholar
Nehaniv, C. L. and Dautenhahn, K. (2000). The correspondence problem. In Dautenhahn, K. and Nehaniv, C. (eds.), Imitation in Animals and Artifacts. Cambridge, MA: MIT Press, 41–61.Google Scholar
Oudeyer, P.-Y. (2002). Phonemic coding might be a result of sensory-motor coupling dynamics. In Hallam, J. (ed.), Proceedings of the 7th International Conference on the Simulation of Adaptive Behavior. Cambridge, MA: MIT Press, 406–16.Google Scholar
Sanleoff, D. and Kruskal, J. B. (1983). Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison, Reading, MA: Addison-Wesley.
Schaal, S. (1999). Is imitation learning the route to humanoid robots?Trends in Cognitive Sciences, 3(6), 233–42.CrossRefGoogle ScholarPubMed
Steels, L. (2000). Language as a complex adaptive system. In Schoenauer, M., Deb, K., Rudolph, G., Yao, X., Lutton, E., Merelo, J. J. and Schwefel, H.-P. (eds.), Proceedings of Parallel Problem Solving from Nature VI, Lecture Notes in Computer Science. Berlin, Germany: Springer.CrossRefGoogle Scholar
Tomasello, M. (1999). The cultural origins of human cognition. Cambridge, MA: Harvard University Press.Google Scholar
Webb, B. (2001). Can robots make good models of biological behavior?Behavioral and Brain Sciences, 24(6), 1033–50.Google Scholar
Whiten, A. and Ham, R. (1992). On the nature and evolution of imitation in the animal kingdom: reappraisal of a century of research. In Slater, P., Rosenblatt, J., Beer, C. and Milinski, M. (eds.), Advances in the Study of Behavior, Vol. 21. San Diego, CA: Academic Press, 239–83.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×